1er commit

.gitignore

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-# ---> Python
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$py.class
-
-# C extensions
-*.so
-
-# Distribution / packaging
-.Python
-env/
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-
-# PyInstaller
-#  Usually these files are written by a python script from a template
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
-
-# Installer logs
-pip-log.txt
-pip-delete-this-directory.txt
-
-# Unit test / coverage reports
-htmlcov/
-.tox/
-.coverage
-.coverage.*
-.cache
-nosetests.xml
-coverage.xml
-*,cover
-.hypothesis/
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-
-# PyBuilder
-target/
-
-# Jupyter Notebook
-.ipynb_checkpoints
-
-# pyenv
-.python-version
-
-# celery beat schedule file
-celerybeat-schedule
-
-# SageMath parsed files
-*.sage.py
-
-# dotenv
-.env
-
-# virtualenv
-.venv
-venv/
-ENV/
-
-# Spyder project settings
-.spyderproject
-
-# Rope project settings
-.ropeproject
-
-# ---> R
-# History files
-.Rhistory
-.Rapp.history
-
-# Session Data files
-.RData
-
-# Example code in package build process
-*-Ex.R
-
-# Output files from R CMD build
-/*.tar.gz
-
-# Output files from R CMD check
-/*.Rcheck/
-
-# RStudio files
-.Rproj.user/
-
-# produced vignettes
-vignettes/*.html
-vignettes/*.pdf
-
-# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
-.httr-oauth
-
-# knitr and R markdown default cache directories
-/*_cache/
-/cache/
-
-# Temporary files created by R markdown
-*.utf8.md
-*.knit.md
-

.ipynb_checkpoints/Untitled-checkpoint.ipynb

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+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

LICENSE

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-Copyright (C) 2006 by Rob Landley <rob@landley.net>
-Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted.
-THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

README.md

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-# tp-apprentissage
-

Untitled.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "ad547a73",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "OSError",
+     "evalue": "[Errno 22] Invalid argument: '.\\\\clustering-benchmark-master\\\\src\\\\main\\resources\\\\datasets\\x07rtificial\\x02d-3c-no123.arff'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mOSError\u001b[0m                                   Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-2-2bb53bd2604e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;31m# data = arff.loadarff(open('file.arff','r'))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0marff\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloadarff\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'.\\clustering-benchmark-master\\src\\main\\resources\\datasets\\artificial\\2d-3c-no123.arff'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'r'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;31mOSError\u001b[0m: [Errno 22] Invalid argument: '.\\\\clustering-benchmark-master\\\\src\\\\main\\resources\\\\datasets\\x07rtificial\\x02d-3c-no123.arff'"
+     ]
+    }
+   ],
+   "source": [
+    "from scipy.io import arff\n",
+    "\n",
+    "# data = arff.loadarff(open('file.arff','r'))\n",
+    "data = arff.loadarff(open('.\\clustering-benchmark-master\\src\\main\\resources\\datasets\\artificial\\2d-3c-no123.arff','r'))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "13b7eb33",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

clustering-benchmark-master/.gitignore

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+*.class
+
+# Package Files #
+*.jar
+*.war
+*.ear
+*~
+.classpath
+.project
+.settings/
+target/
+logs/
+/nbproject/private/
+
+/nbproject/

clustering-benchmark-master/README-old.asc

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+# Clustering datasets
+
+## Datasets
+
+This project contains collection of labeled clustering problems that can be found in the literature. Most of datasets were artificially created.
+
+All datasets can be found link:https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial[data folder].
+
+### 2d-10c
+
+[align="right",options="header"]
+|===
+| data points | clusters | dimension
+| 2990  |  10 |  2
+|===
+
+image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-10c.png["2d-10c",400,float="left"]
+
+[.float .right]
+* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-10c.arff[ARFF]
+* link:https://github.com/deric/handl-data-generators[generator]
+
+> J. Handl and J. Knowles, “Multiobjective clustering with automatic
+> determination of the number of clusters,” UMIST, Tech. Rep., 2004.
+
+### atom
+
+[align="right",options="header"]
+|===
+| data points | clusters | dimension
+| 800         |        2 |  3
+|===
+
+image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/atom.png["atom",400,float="left"]
+
+[.float .right]
+* source: link:https://www.uni-marburg.de/fb12/datenbionik/data?language_sync=1[FCPS]
+* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/atom.arff[ARFF]
+
+### aggregation
+
+[align="right",options="header"]
+|===
+| data points | clusters | dimension
+| 788  |  7 |  2
+|===
+
+image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/aggregation.png[aggregation,400,float="left"]
+
+[.float .right]
+* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/aggregation.arff[ARFF]
+* link:http://cs.joensuu.fi/sipu/datasets/[original source]
+
+> Gionis, A., H. Mannila, and P. Tsaparas, Clustering aggregation.
+> ACM Transactions on Knowledge Discovery from Data (TKDD), 2007. 1(1): p. 1-30.
+
+### chainlink
+
+[align="right",options="header"]
+|===
+| data points | clusters | dimension
+| 1000        |        2 |  3
+|===
+
+image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/chainlink.png["chainlink",400,float="left"]
+
+[.float .right]
+* source: link:https://www.uni-marburg.de/fb12/datenbionik/data?language_sync=1[FCPS]
+* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/chainlink.arff[ARFF]
+
+> Alfred Ultsch, Clustering with SOM: U*C,
+> in Proc. Workshop on Self Organizing Feature Maps ,pp 31-37 Paris 2005.
+
+### D31
+
+[align="right",style="asciidoc",options="noborders,wide"]
+|===
+| data points |  3100
+| clusters    | 31
+| dimensions  | 2
+| image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/D31.png["D31",400,float="left"] | * link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/D31.arff[ARFF]
+|===
+
+> Veenman, C.J., M.J.T. Reinders, and E. Backer,
+> A maximum variance cluster algorithm. IEEE Trans. Pattern Analysis and Machine Intelligence 2002. 24(9): p. 1273-1280.
+
+### 3MC
+
+[align="right",options="header",style="literal"]
+|===
+| data points | clusters | dimension
+| 400         |        3 |  2
+|===
+
+[.float .right]
+image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/3MC.png["3MC",400,float="left"]
+
+
+### DS577
+
+[align="right",options="header"]
+|===
+| data points | clusters | dimension
+| 577        |        3 |  2
+|===
+
+image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/DS577.png["D31",400,float="left"]
+
+[.float .right]
+* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/DS577.arff[ARFF]
+
+> M. C. Su, C. H. Chou, and C. C. Hsieh, “Fuzzy C-Means Algorithm with a Point Symmetry Distance,”
+> International Journal of Fuzzy Systems, vol. 7, no. 4, pp. 175-181, 2005.
+
+
+### cluto-t4_8k
+
+[align="right",options="header"]
+|===
+| data points | clusters | dimension
+| 8000        |        7 |  2
+|===
+
+image::https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t4_8k.png["cluto-t4_8k",400,float="left"]
+
+[.float .right]
+* link:https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cluto-t4.8k.arff[ARFF]
+
+> G. Karypis, “CLUTO A Clustering Toolkit,”
+> Dept. of Computer Science, University of Minnesota, Tech. Rep. 02-017, 2002, available at
+http://www.cs.umn.edu/ ̃cluto.
+
+
+## Experiments
+
+This project contains set of clustering methods benchmarks on various dataset. The project is dependent on [Clueminer project](https://github.com/deric/clueminer).
+
+in order to run benchmark compile dependencies into a single JAR file:
+
+    mvn assembly:assembly
+
+# Consensus experiment
+
+allows running repeated runs of the same algorithm:
+
+```
+./run consensus --dataset "triangle1" --repeat 10
+```
+by default k-means algorithm is used.
+
+For available datasets see [resources folder](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial).

clustering-benchmark-master/README.md

@@ -0,0 +1,139 @@
+# Clustering benchmarks
+
+## Datasets
+
+This project contains collection of labeled clustering problems that can be found in the literature. Most of datasets were artificially created.
+
+The benchmark includes:
+
+  * [artificial datasets](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial)
+  * [real world datasets](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/real-world)
+
+### Artificial data
+
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-10c.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-10c.png" alt="2d-10c" title="2d-10c" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-20c-no0.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-20c-no0.png" alt="2d-20c-no0" title="2d-20c-no0" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-3c-no123.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-3c-no123.png" alt="2d-3c-no123" title="2d-3c-no123" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-4c-no4.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-4c-no4.png" alt="2d-4c-no4" title="2d-4c-no4" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-4c-no9.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-4c-no9.png" alt="2d-4c-no9" title="2d-4c-no9" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2d-4c.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2d-4c.png" alt="2d-4c" title="2d-4c" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/2sp2glob.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/2sp2glob.png" alt="2sp2glob" title="2sp2glob" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/3-spiral.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/3-spiral.png" alt="3-spiral" title="3-spiral" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/3MC.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/3mc.png" alt="3MC" title="3MC" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/D31.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/d31.png" alt="D31" title="D31" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/DS577.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/ds577.png" alt="DS577" title="DS577" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/DS850.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/ds850.png" alt="DS850" title="DS850" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/R15.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/r15.png" alt="R15" title="R15" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/aggregation.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/aggregation.png" alt="aggregation" title="aggregation" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/atom.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/atom.png" alt="atom" title="atom" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/banana.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/banana.png" alt="banana" title="banana" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/birch-rg1.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/birch-rg1.png" alt="birch-rg1" title="birch-rg1" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/birch-rg2.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/birch-rg2.png" alt="birch-rg2" title="birch-rg2" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/birch-rg3.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/birch-rg3.png" alt="birch-rg3" title="birch-rg3" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/chainlink.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/chainlink.png" alt="chainlink" title="chainlink" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cluto-t4.8k.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t4.8k.png" alt="cluto-t4.8k" title="cluto-t4.8k" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cluto-t5.8k.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t5.8k.png" alt="cluto-t5.8k" title="cluto-t5.8k" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cluto-t7.10k.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t7.10k.png" alt="cluto-t7.10k" title="cluto-t7.10k" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cluto-t8.8k.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cluto-t8.8k.png" alt="cluto-t8.8k" title="cluto-t8.8k" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/complex8.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/complex8.png" alt="complex8" title="complex8" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/complex9.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/complex9.png" alt="complex9" title="complex9" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/compound.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/compound.png" alt="compound" title="compound" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cure-t0-2000n-2D.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cure-t0-2000n-2d.png" alt="cure-t0-2000n-2D" title="cure-t0-2000n-2D" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/cure-t1-2000n-2D.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/cure-t1-2000n-2d.png" alt="cure-t1-2000n-2D" title="cure-t1-2000n-2D" width="239px" style="max-width: 100%;float:left;"/></a>
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+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/twodiamonds.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/twodiamonds.png" alt="twodiamonds" title="twodiamonds" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/wingnut.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/wingnut.png" alt="wingnut" title="wingnut" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/xclara.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/xclara.png" alt="xclara" title="xclara" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/zelnik1.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik1.png" alt="zelnik1" title="zelnik1" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/zelnik2.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik2.png" alt="zelnik2" title="zelnik2" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/zelnik3.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik3.png" alt="zelnik3" title="zelnik3" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/zelnik4.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik4.png" alt="zelnik4" title="zelnik4" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/zelnik5.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik5.png" alt="zelnik5" title="zelnik5" width="239px" style="max-width: 100%;float:left;"/></a>
+<a href="https://github.com/deric/clustering-benchmark/blob/master/src/main/resources/datasets/artificial/zelnik6.arff"><img src="https://github.com/deric/clustering-benchmark/blob/images/fig/artificial/zelnik6.png" alt="zelnik6" title="zelnik6" width="239px" style="max-width: 100%;float:left;"/></a>
+
+
+## Experiments
+
+This project contains set of clustering methods benchmarks on various dataset. The project is dependent on [Clueminer project](https://github.com/deric/clueminer).
+
+in order to run benchmark compile dependencies into a single JAR file:
+
+    mvn assembly:assembly
+
+# Consensus experiment
+
+allows running repeated runs of the same algorithm:
+
+```
+./run consensus --dataset "triangle1" --repeat 10
+```
+by default k-means algorithm is used.
+
+For available datasets see [resources folder](https://github.com/deric/clustering-benchmark/tree/master/src/main/resources/datasets/artificial).

clustering-benchmark-master/consensus

@@ -0,0 +1,6 @@
+#!/bin/bash
+meth=("KmB-COMUSA-RAND" "KmB-COMUSA-MO" "KmB-COMUSA-RAND-fixed")
+for m in "${meth[@]}"; do
+ ./run consensus --repeat 10 --method "$m" --dataset "$@"
+done
+

clustering-benchmark-master/evolve-sc

@@ -0,0 +1,3 @@
+#!/bin/bash
+ARGS="evolve-sc --test --generations 20 --population 50 $@"
+`./run $ARGS`

clustering-benchmark-master/nb-configuration.xml

@@ -0,0 +1,21 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project-shared-configuration>
+    <!--
+This file contains additional configuration written by modules in the NetBeans IDE.
+The configuration is intended to be shared among all the users of project and
+therefore it is assumed to be part of version control checkout.
+Without this configuration present, some functionality in the IDE may be limited or fail altogether.
+-->
+    <spellchecker-wordlist xmlns="http://www.netbeans.org/ns/spellchecker-wordlist/1">
+        <word>unsupervised</word>
+    </spellchecker-wordlist>
+    <properties xmlns="http://www.netbeans.org/ns/maven-properties-data/1">
+        <!--
+Properties that influence various parts of the IDE, especially code formatting and the like. 
+You can copy and paste the single properties, into the pom.xml file and the IDE will pick them up.
+That way multiple projects can share the same settings (useful for formatting rules for example).
+Any value defined here will override the pom.xml file value but is only applicable to the current project.
+-->
+        <netbeans.hint.licensePath>${project.basedir}/../clueminer/license.txt</netbeans.hint.licensePath>
+    </properties>
+</project-shared-configuration>

clustering-benchmark-master/pom.xml

@@ -0,0 +1,246 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <modelVersion>4.0.0</modelVersion>
+    <parent>
+        <artifactId>clueminer-parent</artifactId>
+        <groupId>org.clueminer</groupId>
+        <version>0.1.0-SNAPSHOT</version>
+        <relativePath>../..</relativePath>
+    </parent>
+
+    <groupId>org.clueminer</groupId>
+    <artifactId>clustering-benchmark</artifactId>
+    <version>0.1.0-SNAPSHOT</version>
+    <packaging>nbm</packaging>
+
+    <name>clustering-benchmark</name>
+
+    <properties>
+        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+    </properties>
+
+    <repositories>
+        <!--
+        Repository hosting NetBeans modules, especially APIs.
+        Versions are based on IDE releases, e.g.: RELEASE691
+        To create your own repository, use: nbm:populate-repository
+        -->
+        <repository>
+            <id>netbeans</id>
+            <name>NetBeans</name>
+            <url>http://bits.netbeans.org/maven2/</url>
+            <snapshots>
+                <enabled>false</enabled>
+            </snapshots>
+        </repository>
+    </repositories>
+
+    <dependencies>
+        <dependency>
+            <groupId>org.netbeans.api</groupId>
+            <artifactId>org-netbeans-api-annotations-common</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>dataset-api</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>clustering-impl</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>clustering-api</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>dataset-impl</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>dataset-io</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>fixtures</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>dataset-benchmark</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>org.netbeans.api</groupId>
+            <artifactId>org-openide-util-lookup</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>org.netbeans.api</groupId>
+            <artifactId>org-openide-util</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>utils</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>clustering-evolution</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>clustering-eval</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>clustering-dist</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>fixtures-clustering</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>junit</groupId>
+            <artifactId>junit</artifactId>
+            <version>${clueminer.junit.version}</version>
+            <scope>test</scope>
+        </dependency>
+        <dependency>
+            <groupId>com.beust</groupId>
+            <artifactId>jcommander</artifactId>
+            <version>1.48</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>core-lib-wrapper</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>evolution-api</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>org.clueminer</groupId>
+            <artifactId>chameleon</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>gnuplot</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>partitioning-api</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>graph-api</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>graph-impl</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>${project.groupId}</groupId>
+            <artifactId>partitioning-impl</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>org.netbeans.api</groupId>
+            <artifactId>org-openide-util-ui</artifactId>
+        </dependency>
+    </dependencies>
+
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>org.codehaus.mojo</groupId>
+                <artifactId>nbm-maven-plugin</artifactId>
+                <extensions>true</extensions>
+                <configuration>
+                    <publicPackages>
+                        <publicPackage>org.clueminer.clustering.benchmark</publicPackage>
+                        <publicPackage>org.clueminer.data</publicPackage>
+                    </publicPackages>
+                </configuration>
+            </plugin>
+
+            <plugin>
+                <!-- NetBeans 6.9+ requires JDK 6 -->
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-compiler-plugin</artifactId>
+                <version>${maven.compiler}</version>
+                <configuration>
+                    <source>1.8</source>
+                    <target>1.8</target>
+                    <archive>
+                        <manifest>
+                            <mainClass>org.clueminer.clustering.benchmark.Main</mainClass>
+                            <packageName>org.clueminer.clustering.benchmark</packageName>
+                            <addClasspath>true</addClasspath>
+                        </manifest>
+                    </archive>
+                </configuration>
+            </plugin>
+
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-jar-plugin</artifactId>
+                <version>2.4</version>
+                <configuration>
+                    <!-- to have the jar plugin pickup the nbm generated manifest -->
+                    <useDefaultManifestFile>true</useDefaultManifestFile>
+                    <archive>
+                        <manifest>
+                            <mainClass>org.clueminer.clustering.benchmark.Main</mainClass>
+                            <packageName>org.clueminer.clustering.benchmark</packageName>
+                            <addClasspath>true</addClasspath>
+                        </manifest>
+                    </archive>
+                </configuration>
+            </plugin>
+            <plugin>
+                <artifactId>maven-assembly-plugin</artifactId>
+                <configuration>
+                    <descriptorRefs>
+                        <descriptorRef>jar-with-dependencies</descriptorRef>
+                    </descriptorRefs>
+                    <archive>
+                        <manifest>
+                            <mainClass>org.clueminer.clustering.benchmark.Main</mainClass>
+                        </manifest>
+                    </archive>
+                </configuration>
+            </plugin>
+            <plugin>
+                <artifactId>maven-dependency-plugin</artifactId>
+                <executions>
+                    <execution>
+                        <phase>install</phase>
+                        <goals>
+                            <goal>copy-dependencies</goal>
+                        </goals>
+                        <configuration>
+                            <outputDirectory>${project.build.directory}/lib</outputDirectory>
+                        </configuration>
+                    </execution>
+                </executions>
+            </plugin>
+
+        </plugins>
+    </build>
+</project>

clustering-benchmark-master/run

@@ -0,0 +1,9 @@
+#!/bin/bash
+ARGS="$@"
+MAIN="org.clueminer.clustering.benchmark.Main"
+jarfile="$(ls -t target/*jar-with-dependencies.jar | head -1)"
+if [[ -f "$jarfile" ]]; then
+  java -jar $jarfile $ARGS
+else
+  mvn "-Dexec.args=-classpath %classpath $MAIN $ARGS" -Dexec.executable=java -Dexec.classpathScope=runtime org.codehaus.mojo:exec-maven-plugin:1.2.1:exec
+fi

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/AbsParams.java

@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import com.beust.jcommander.Parameter;
+import java.io.File;
+import org.clueminer.utils.FileUtils;
+import org.openide.util.NbBundle;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class AbsParams {
+
+    @Parameter(names = "--dir", description = "directory for results", required = false)
+    public String home = System.getProperty("user.home") + File.separatorChar
+            + NbBundle.getMessage(FileUtils.class, "FOLDER_Home");
+
+    @Parameter(names = "--repeat", description = "number of repetitions of each experiment")
+    public int repeat = 5;
+
+    @Parameter(names = "--log", description = "java log level")
+    public String log = "INFO";
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/Bench.java

@@ -0,0 +1,104 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import com.beust.jcommander.JCommander;
+import com.beust.jcommander.ParameterException;
+import java.io.File;
+import java.util.HashMap;
+import java.util.Map;
+import org.clueminer.data.DataLoader;
+import org.clueminer.dataset.api.DataProvider;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.benchmark.DatasetFixture;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public abstract class Bench {
+
+    protected static String benchmarkFolder;
+    protected HashMap<String, Map.Entry<Dataset<? extends Instance>, Integer>> availableDatasets = new HashMap<>();
+    protected DataProvider provider;
+
+    public Bench() {
+        //constructor without arguments
+    }
+
+    public static void ensureFolder(String folder) {
+        File file = new File(folder);
+        if (!file.exists()) {
+            if (file.mkdirs()) {
+                System.out.println("Directory " + folder + " created!");
+            } else {
+                System.out.println("Failed to create " + folder + "directory!");
+            }
+        }
+    }
+
+    public abstract void main(String[] args);
+
+    public static void printUsage(String[] args, JCommander cmd, AbsParams params) {
+
+        try {
+            cmd.parse(args);
+
+        } catch (ParameterException ex) {
+            System.out.println(ex.getMessage());
+            cmd.usage();
+            System.exit(0);
+        }
+    }
+
+    protected void loadDatasets() {
+        Map<Dataset<? extends Instance>, Integer> datasets = DatasetFixture.allDatasets();
+        for (Map.Entry<Dataset<? extends Instance>, Integer> entry : datasets.entrySet()) {
+            Dataset<? extends Instance> d = entry.getKey();
+            availableDatasets.put(d.getName(), entry);
+        }
+    }
+
+    protected void loadBenchArtificial() {
+        provider = DataLoader.createLoader("datasets", "artificial");
+    }
+
+    protected void loadBenchRealWorld() {
+        provider = DataLoader.createLoader("datasets", "real-world");
+    }
+
+    /**
+     * Load specific dataset by name
+     *
+     * @param name
+     */
+    protected void load(String name) {
+        Map<Dataset<? extends Instance>, Integer> datasets = DatasetFixture.allDatasets();
+        for (Map.Entry<Dataset<? extends Instance>, Integer> entry : datasets.entrySet()) {
+            Dataset<? extends Instance> d = entry.getKey();
+            if (d.getName().equalsIgnoreCase(name)) {
+                availableDatasets.put(d.getName(), entry);
+            }
+        }
+    }
+
+    public static String safeName(String name) {
+        return name.toLowerCase().replace(" ", "_");
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/BenchParams.java

@@ -0,0 +1,42 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import com.beust.jcommander.Parameter;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class BenchParams extends AbsParams {
+
+    @Parameter(names = "--n", description = "size of biggest dataset", required = false)
+    public int n = 20;
+
+    @Parameter(names = "--n-small", description = "size of smallest", required = false)
+    public int nSmall = 5;
+
+    @Parameter(names = "--steps", description = "number of datasets which will be generated")
+    public int steps = 4;
+
+    @Parameter(names = "--dimension", description = "number of attributes of each dataset")
+    public int dimension = 5;
+
+    @Parameter(names = "--linkage", description = "linkage method")
+    public String linkage = "Single Linkage";
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/ClusteringBenchmark.java

@@ -0,0 +1,63 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import org.clueminer.clustering.aggl.linkage.CompleteLinkage;
+import org.clueminer.clustering.aggl.linkage.SingleLinkage;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import org.clueminer.clustering.api.AlgParams;
+import org.clueminer.clustering.api.ClusteringAlgorithm;
+import org.clueminer.clustering.api.ClusteringFactory;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.utils.Props;
+
+/**
+ * Execute single clustering
+ *
+ * @author Tomas Barton
+ * @param <E>
+ */
+public class ClusteringBenchmark<E extends Instance> {
+
+    public Container<E> cluster(Dataset<E> dataset, Props props) {
+        ClusteringFactory cf = ClusteringFactory.getInstance();
+        ClusteringAlgorithm algorithm = cf.getProvider(props.get(AlgParams.ALG));
+
+        return new Container(algorithm, dataset, props);
+    }
+
+    public Container<E> cluster(ClusteringAlgorithm algorithm, Dataset<E> dataset, Props props) {
+        return new Container(algorithm, dataset, props);
+    }
+
+    public Container<E> hclust(final AgglomerativeClustering algorithm, final Dataset<E> dataset, final String linkage) {
+        Props props = new Props();
+        props.put(AlgParams.LINKAGE, linkage);
+        final Container<E> runnable = new Container(algorithm, dataset, props);
+        return runnable;
+    }
+
+    public Container<E> singleLinkage(final AgglomerativeClustering algorithm, final Dataset<E> dataset) {
+        return hclust(algorithm, dataset, SingleLinkage.name);
+    }
+
+    public Container<E> completeLinkage(final AgglomerativeClustering algorithm, final Dataset<E> dataset) {
+        return hclust(algorithm, dataset, CompleteLinkage.name);
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/Container.java

@@ -0,0 +1,86 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import org.clueminer.clustering.TreeDiff;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import org.clueminer.clustering.api.AlgParams;
+import org.clueminer.clustering.api.Clustering;
+import org.clueminer.clustering.api.ClusteringAlgorithm;
+import org.clueminer.clustering.api.ClusteringType;
+import org.clueminer.clustering.api.HierarchicalResult;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.exec.ClusteringExecutorCached;
+import org.clueminer.utils.Props;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ *
+ * @author Tomas Barton
+ * @param <E>
+ */
+public class Container<E extends Instance> implements Runnable {
+
+    private HierarchicalResult result;
+    private Clustering clustering;
+    private final Dataset<E> dataset;
+    private Props params;
+    private static final Logger LOG = LoggerFactory.getLogger(Container.class);
+    private ClusteringExecutorCached executor;
+
+    public Container(ClusteringAlgorithm algorithm, Dataset<E> dataset) {
+        this.executor = new ClusteringExecutorCached();
+        executor.setAlgorithm(algorithm);
+        this.dataset = dataset;
+        this.params = new Props();
+    }
+
+    public Container(ClusteringAlgorithm algorithm, Dataset<E> dataset, Props params) {
+        this.executor = new ClusteringExecutorCached();
+        executor.setAlgorithm(algorithm);
+        this.dataset = dataset;
+        this.params = params;
+    }
+
+    public HierarchicalResult hierarchical(AgglomerativeClustering algorithm, Dataset<E> dataset, Props params) {
+        params.put(AlgParams.CLUSTERING_TYPE, ClusteringType.ROWS_CLUSTERING);
+        return algorithm.hierarchy(dataset, params);
+    }
+
+    @Override
+    public void run() {
+        if (executor.getAlgorithm() instanceof AgglomerativeClustering) {
+            this.result = executor.hclustRows(dataset, params);
+        } else {
+            this.clustering = executor.clusterRows(dataset, params);
+        }
+    }
+
+    public Clustering cluster(ClusteringAlgorithm algorithm, Dataset<E> dataset, Props params) {
+        return executor.clusterRows(dataset, params);
+    }
+
+    public boolean equals(Container other) {
+        if (this.result == null || other.result == null) {
+            throw new RuntimeException("got null result. this = " + result + " other = " + other);
+        }
+        return TreeDiff.compare(this.result, other.result);
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/Experiment.java

@@ -0,0 +1,127 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import java.util.Random;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import org.clueminer.clustering.api.ClusteringAlgorithm;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.impl.ArrayDataset;
+import org.clueminer.report.NanoBench;
+import org.clueminer.utils.Props;
+import org.openide.util.Exceptions;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ *
+ * @author Tomas Barton
+ * @param <E>
+ */
+public class Experiment<E extends Instance> implements Runnable {
+
+    protected final Random rand;
+    protected final BenchParams params;
+    private ClusteringAlgorithm[] algorithms;
+    protected final String results;
+    private static final Logger LOG = LoggerFactory.getLogger(Experiment.class);
+
+    public Experiment(BenchParams params, String results) {
+        rand = new Random();
+        this.params = params;
+        this.results = results;
+    }
+
+    public Experiment(BenchParams params, String results, ClusteringAlgorithm[] algorithms) {
+        rand = new Random();
+        this.params = params;
+        this.results = results;
+        this.algorithms = algorithms;
+    }
+
+    @Override
+    public void run() {
+        int inc = (params.n - params.nSmall) / params.steps;
+
+        String[] names = new String[algorithms.length];
+        int j = 0;
+        for (ClusteringAlgorithm alg : algorithms) {
+            names[j++] = alg.getName();
+        }
+
+        GnuplotReporter reporter = new GnuplotReporter(results,
+                new String[]{"algorithm", "linkage", "n"}, names, params.nSmall + "-" + params.n,
+                10);
+        LOG.info("increment = {}", inc);
+        ClusteringBenchmark bench = new ClusteringBenchmark();
+        Container container;
+        AgglomerativeClustering aggl;
+        for (int i = params.nSmall; i <= params.n; i += inc) {
+            Dataset<E> dataset = generateData(i, params.dimension);
+            for (ClusteringAlgorithm alg : algorithms) {
+                String[] opts = new String[]{alg.getName(), params.linkage, String.valueOf(dataset.size())};
+
+                if (alg instanceof AgglomerativeClustering) {
+                    aggl = (AgglomerativeClustering) alg;
+                    container = bench.hclust(aggl, dataset, params.linkage);
+                } else {
+                    container = bench.cluster(alg, dataset, new Props());
+                }
+
+                NanoBench.create().measurements(params.repeat).collect(reporter, opts).measure(
+                        alg.getName() + " - " + dataset.size(),
+                        container
+                );
+                // Get the Java runtime
+                Runtime runtime = Runtime.getRuntime();
+                // Run the garbage collector
+                runtime.gc();
+                try {
+                    Thread.sleep(1000);
+                } catch (InterruptedException ex) {
+                    Exceptions.printStackTrace(ex);
+                }
+            }
+        }
+        reporter.finish();
+    }
+
+    /**
+     * Generate random dataset of doubles with given dimensions
+     *
+     * @param size
+     * @param dim
+     * @return
+     */
+    public Dataset<E> generateData(int size, int dim) {
+        LOG.info("generating data: {}x{}", size, dim);
+        Dataset<E> dataset = new ArrayDataset<>(size, dim);
+        for (int i = 0; i < dim; i++) {
+            dataset.attributeBuilder().create("attr-" + i, "NUMERIC");
+        }
+        for (int i = 0; i < size; i++) {
+            dataset.instance(i).setName(String.valueOf(i));
+            for (int j = 0; j < dim; j++) {
+                dataset.set(i, j, rand.nextDouble());
+            }
+        }
+
+        return dataset;
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/GnuplotReporter.java

@@ -0,0 +1,232 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import com.google.common.collect.ObjectArrays;
+import java.io.File;
+import java.io.FileNotFoundException;
+import java.io.IOException;
+import java.io.PrintWriter;
+import java.io.UnsupportedEncodingException;
+import java.util.LinkedList;
+import org.clueminer.gnuplot.GnuplotHelper;
+import org.clueminer.gnuplot.PointTypeIterator;
+import org.clueminer.report.BigORes;
+import org.clueminer.report.Reporter;
+import org.openide.util.Exceptions;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class GnuplotReporter extends GnuplotHelper implements Reporter {
+
+    private final String dataDir;
+    private final File dataFile;
+    private final LinkedList<String> plots;
+
+    public GnuplotReporter(String folder, String[] opts, String[] algorithms, String suffix, int xCol) {
+        this.dataDir = folder + File.separatorChar + "data";
+        mkdir(dataDir);
+        this.dataFile = new File(dataDir + File.separatorChar + "results-" + suffix + ".csv");
+        this.plots = new LinkedList<>();
+        writeHeader(opts);
+
+        String memPath = dataDir + File.separatorChar + "mem" + suffix + ".gpt";
+        String cpuPath = dataDir + File.separatorChar + "cpu" + suffix + ".gpt";
+        String cpu2Path = dataDir + File.separatorChar + "cpu2" + suffix + ".gpt";
+        String tpsPath = dataDir + File.separatorChar + "tps" + suffix + ".gpt";
+        String timePath = dataDir + File.separatorChar + "time" + suffix + ".gpt";
+
+        writePlotScript(new File(memPath),
+                plotComplexity(8, "memory (kB)", xCol, 7, dataFile.getName(), algorithms, "Memory usage of hierarchical clustering algorithms - " + opts[1], false));
+        writePlotScript(new File(cpuPath),
+                plotCpu(8, "CPU", xCol, 2, dataFile.getName(), algorithms, "CPU usage of hierarchical clustering algorithms - " + opts[1], false));
+        writePlotScript(new File(cpu2Path),
+                plotComplexity(8, "CPU time", xCol, 2, dataFile.getName(), algorithms, "CPU usage of hierarchical clustering algorithms - " + opts[1], false));
+        writePlotScript(new File(tpsPath),
+                plotComplexity(8, "tps", xCol, 5, dataFile.getName(), algorithms, "Transactuion per second - " + opts[1], true));
+
+        writePlotScript(new File(timePath),
+                plotComplexity(8, "time", xCol, 4, dataFile.getName(), algorithms, "Execution time - " + opts[1], true));
+
+        writeBashScript(folder);
+    }
+
+    private void writeHeader(String[] opts) {
+        String[] head = new String[]{"label", "avg time (ms)", "memory (MB)", "total time (s)", "tps", "repeats", "memory (kB)"};
+        String[] line = ObjectArrays.concat(head, opts, String.class);
+        writeCsvLine(dataFile, line, false);
+    }
+
+    /**
+     *
+     * @param result
+     */
+    @Override
+    public void finalResult(BigORes result) {
+        String[] res = new String[]{result.getLabel(), result.avgTimeMs(),
+            result.totalMemoryInMb(), result.totalTimeInS(), result.tps(),
+            result.measurements(), result.totalMemoryInKb()
+        };
+        String[] line = ObjectArrays.concat(res, result.getOpts(), String.class);
+        writeCsvLine(dataFile, line, true);
+    }
+
+    /**
+     *
+     * @param file     to write Gnuplot script
+     * @param dataFile
+     * @param labelPos column of label which is used for data rows in chart
+     * @param type
+     * @param x
+     * @param y
+     */
+    private void writePlotScript(File file, String script) {
+        PrintWriter template;
+        try {
+            template = new PrintWriter(file, "UTF-8");
+            template.write(script);
+            template.close();
+        } catch (FileNotFoundException | UnsupportedEncodingException ex) {
+            Exceptions.printStackTrace(ex);
+        }
+        plots.add(withoutExtension(file));
+    }
+
+    private String plotCpu(int labelPos, String yLabel, int x, int y, String dataFile, String[] algorithms, String title, boolean logscale) {
+        String res = "set datafile separator \",\"\n"
+                + "set key outside bottom horizontal box\n"
+                + "set title \"" + title + "\"\n"
+                + "set xlabel \"data size\" font \"Times,12\"\n"
+                + "set ylabel \"" + yLabel + "\" font \"Times,12\"\n"
+                //   + "set xtics 0,0.5 nomirror\n"
+                //   + "set ytics 0,0.5 nomirror\n"
+                + "set mytics 2\n"
+                + "set mx2tics 2\n"
+                + "set grid\n"
+                + "set pointsize 0.5\n"
+                + "f(x) = 0.5 * x**2\n";
+        if (logscale) {
+            res += "set logscale y 2\n";
+        }
+        int i = 0;
+        PointTypeIterator pti = new PointTypeIterator();
+        for (String alg : algorithms) {
+            if (i == 0) {
+                res += "plot ";
+            }
+            res += "\"< awk -F\\\",\\\" '{if($" + labelPos + " == \\\"" + alg
+                    + "\\\") print}' " + dataFile + "\" u " + x + ":" + y
+                    + " t \"" + alg + "\" w linespoints pt " + pti.next();
+            res += ", \\\n";
+            i++;
+        }
+        res += "f(x) title 'x^2' with lines linestyle 18\n";
+        return res;
+    }
+
+    private String plotComplexity(int labelPos, String yLabel, int x, int y, String dataFile, String[] algorithms, String title, boolean logscale) {
+        String res = "set datafile separator \",\"\n"
+                + "set key outside bottom horizontal box\n"
+                + "set title \"" + title + "\"\n"
+                + "set xlabel \"data size\" font \"Times,12\"\n"
+                + "set ylabel \"" + yLabel + "\" font \"Times,12\"\n"
+                //   + "set xtics 0,0.5 nomirror\n"
+                //   + "set ytics 0,0.5 nomirror\n"
+                + "set mytics 2\n"
+                + "set mx2tics 2\n"
+                + "set grid\n"
+                + "set pointsize 0.5\n";
+        if (logscale) {
+            res += "set logscale y 2\n";
+        }
+        int i = 0;
+        int last = algorithms.length - 1;
+        PointTypeIterator pti = new PointTypeIterator();
+        for (String alg : algorithms) {
+            if (i == 0) {
+                res += "plot ";
+            }
+            res += "\"< awk -F\\\",\\\" '{if($" + labelPos + " == \\\"" + alg
+                    + "\\\") print}' " + dataFile + "\" u " + x + ":" + y
+                    + " t \"" + alg + "\" w linespoints pt " + pti.next();
+            if (i != last) {
+                res += ", \\\n";
+            } else {
+                res += "\n";
+            }
+
+            i++;
+        }
+        return res;
+    }
+
+    /**
+     * Should be called when all plot files are written
+     */
+    public void finish() {
+        //TODO maybe some cleanup?
+    }
+
+    private void writeBashScript(String dataDir) {
+        try {
+            bashPlotScript(plots.toArray(new String[plots.size()]), dataDir, "data", "set term pdf font 'Times-New-Roman,8'", "pdf");
+            bashPlotScript(plots.toArray(new String[plots.size()]), dataDir, "data", "set terminal pngcairo size 1024,768 enhanced font 'Verdana,10'", "png");
+
+        } catch (FileNotFoundException ex) {
+            Exceptions.printStackTrace(ex);
+        } catch (UnsupportedEncodingException ex) {
+            Exceptions.printStackTrace(ex);
+        } catch (IOException ex) {
+            Exceptions.printStackTrace(ex);
+        }
+    }
+
+    /**
+     *
+     * @param plots      plot names without extension
+     * @param dir        base dir
+     * @param gnuplotDir directory with gnuplot file
+     * @param term
+     * @param ext        extentions of output format
+     * @throws FileNotFoundException
+     * @throws UnsupportedEncodingException
+     * @throws IOException
+     */
+    public static void bashPlotScript(String[] plots, String dir, String gnuplotDir, String term, String ext)
+            throws FileNotFoundException, UnsupportedEncodingException, IOException {
+        //bash script to generate results
+        String shFile = dir + File.separatorChar + "_plot-" + ext;
+        try (PrintWriter template = new PrintWriter(shFile, "UTF-8")) {
+            template.write(bashTemplate(gnuplotDir));
+            template.write("TERM=\"" + term + "\"\n");
+            int pos;
+            for (String plot : plots) {
+                pos = plot.indexOf(".");
+                if (pos > 0) {
+                    //remove extension part
+                    plot = plot.substring(0, pos);
+                }
+                template.write("gnuplot -e \"${TERM}\" " + plot + gnuplotExtension
+                        + " > $PWD" + File.separatorChar + ".." + File.separatorChar + plot + "." + ext + "\n");
+            }
+        }
+        Runtime.getRuntime().exec("chmod u+x " + shFile);
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/Main.java

@@ -0,0 +1,94 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.Map;
+import org.clueminer.clustering.benchmark.chameleon2.Cham2Bench;
+import org.clueminer.clustering.benchmark.consensus.ConsensusExp;
+import org.clueminer.clustering.benchmark.cutoff.CutoffExp;
+import org.clueminer.clustering.benchmark.exp.Data;
+import org.clueminer.clustering.benchmark.exp.EvolveScores;
+import org.clueminer.clustering.benchmark.exp.HclusPar;
+import org.clueminer.clustering.benchmark.exp.HclusPar2;
+import org.clueminer.clustering.benchmark.exp.Hclust;
+import org.clueminer.clustering.benchmark.gen.NsgaGen;
+import org.clueminer.clustering.benchmark.nsga.NsgaScore;
+import org.clueminer.clustering.benchmark.partition.PartitionExp;
+
+/**
+ *
+ * @author deric
+ */
+public class Main {
+
+    private static final Map<String, Bench> map = new HashMap<>();
+    private static Main instance;
+
+    public Main() {
+        map.put("hclust", new Hclust());
+        map.put("data", new Data());
+        map.put("hclust-par", new HclusPar());
+        map.put("hclust-par2", new HclusPar2());
+        map.put("evolve-sc", new EvolveScores());
+        map.put("nsga", new NsgaScore());
+        map.put("nsga-gen", new NsgaGen());
+        map.put("consensus", new ConsensusExp());
+        map.put("cutoff", new CutoffExp());
+        map.put("partition", new PartitionExp());
+        map.put("chameleon2", new Cham2Bench());
+    }
+
+    /**
+     * Entrypoint to all experiments
+     *
+     * @param args the command line arguments
+     */
+    public static void main(String[] args) {
+        if (instance == null) {
+            instance = new Main();
+        }
+        if (args.length == 0) {
+            usage();
+        }
+        String exp = args[0];
+        if (!Main.map.containsKey(exp)) {
+            usage();
+        }
+
+        String[] other = Arrays.copyOfRange(args, 1, args.length);
+        Bench bench = Main.map.get(exp);
+        //run it
+        bench.main(other);
+    }
+
+    private static void usage() {
+        System.out.println("Usage: java -jar {jar name} [experiment name] [[optional arguments]]");
+        System.out.println("Valid experriments values are:");
+        for (String key : map.keySet()) {
+            for (int i = 0; i < 5; i++) {
+                System.out.print(" ");
+            }
+            System.out.print("- " + key + "\n");
+        }
+        System.out.println("use '[experiment] --help' to find out more about optional arguments");
+        System.out.println("--------------------------");
+        System.exit(1);
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/ParamExperiment.java

@@ -0,0 +1,89 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark;
+
+import org.clueminer.clustering.api.AlgParams;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.report.NanoBench;
+import org.clueminer.utils.Props;
+import org.openide.util.Exceptions;
+
+/**
+ *
+ * @author deric
+ * @param <E>
+ */
+public class ParamExperiment<E extends Instance> extends Experiment<E> {
+
+    private Props[] configs;
+
+    public ParamExperiment(BenchParams params, String results) {
+        super(params, results);
+    }
+
+    public ParamExperiment(BenchParams params, String results, Props[] configs) {
+        super(params, results);
+
+        this.configs = configs;
+    }
+
+    @Override
+    public void run() {
+        int inc = (params.n - params.nSmall) / params.steps;
+
+        String[] names = new String[configs.length];
+        int j = 0;
+        for (Props alg : configs) {
+            names[j++] = alg.get(AlgParams.ALG);
+        }
+
+        //json props must be last column (in order to avoid issues with gnuplot parsing commas in json)
+        GnuplotReporter reporter = new GnuplotReporter(results,
+                new String[]{"algorithm", "n", "config"},
+                names, params.nSmall + "-" + params.n, 9);
+        System.out.println("increment = " + inc);
+        ClusteringBenchmark bench = new ClusteringBenchmark();
+        Container container;
+        for (int i = params.nSmall; i <= params.n; i += inc) {
+            Dataset<E> dataset = generateData(i, params.dimension);
+            for (Props props : configs) {
+                String[] opts = new String[]{props.get(AlgParams.ALG), String.valueOf(dataset.size()), props.toJson()};
+                try {
+                    container = bench.cluster(dataset, props);
+                    NanoBench.create().measurements(params.repeat).collect(reporter, opts).measure(
+                            props.get(AlgParams.ALG) + " - " + dataset.size(),
+                            container
+                    );
+                } catch (Exception ex) {
+                    Exceptions.printStackTrace(ex);
+                }
+                // Get the Java runtime
+                Runtime runtime = Runtime.getRuntime();
+                // Run the garbage collector
+                runtime.gc();
+                try {
+                    Thread.sleep(1000);
+                } catch (InterruptedException ex) {
+                    Exceptions.printStackTrace(ex);
+                }
+            }
+        }
+        reporter.finish();
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/chameleon2/Cham2Bench.java

@@ -0,0 +1,74 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.chameleon2;
+
+import java.io.File;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.api.AlgParams;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import org.clueminer.clustering.benchmark.BenchParams;
+import org.clueminer.clustering.benchmark.ParamExperiment;
+import org.clueminer.clustering.benchmark.exp.Hclust;
+import org.clueminer.log.ClmLog;
+import org.clueminer.utils.Props;
+
+/**
+ *
+ * @author deric
+ */
+public class Cham2Bench extends Hclust {
+
+    /**
+     * @param args the command line arguments
+     */
+    @Override
+    public void main(String[] args) {
+        BenchParams params = parseArguments(args);
+        ClmLog.setup(params.log);
+
+        benchmarkFolder = params.home + File.separatorChar + "chameleon2";
+        ensureFolder(benchmarkFolder);
+
+        System.out.println("# n = " + params.n);
+        System.out.println("=== starting experiment:");
+
+        Props ch2 = new Props();
+        ch2.put(AlgParams.ALG, "Chameleon");
+
+        Props hc = new Props();
+        hc.put(AlgParams.ALG, "HC-LW(ms)");
+        hc.put(AlgParams.LINKAGE, "Single");
+
+        Props dbscan = new Props();
+        dbscan.put(AlgParams.ALG, "DBSCAN");
+
+        Props km = new Props();
+        km.put(AlgParams.ALG, "k-means");
+
+        Props[] algorithms = new Props[]{
+            ch2,
+            hc,
+            dbscan, km
+        };
+        ParamExperiment exp = new ParamExperiment(params, benchmarkFolder, algorithms);
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/consensus/ConsensusExp.java

@@ -0,0 +1,60 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.consensus;
+
+import com.beust.jcommander.JCommander;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.benchmark.Bench;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.printUsage;
+import org.clueminer.log.ClmLog;
+
+/**
+ *
+ * @author deric
+ */
+public class ConsensusExp extends Bench {
+
+    public static final String name = "consensus";
+
+    protected static ConsensusParams parseArguments(String[] args) {
+        ConsensusParams params = new ConsensusParams();
+        JCommander cmd = new JCommander(params);
+        printUsage(args, cmd, params);
+        return params;
+    }
+
+    @Override
+    public void main(String[] args) {
+        ConsensusParams params = parseArguments(args);
+        ClmLog.setup(params.log);
+
+        loadBenchArtificial();
+        System.out.println("dataset: " + params.dataset);
+
+        benchmarkFolder = params.home + '/' + "benchmark" + '/' + name;
+        ensureFolder(benchmarkFolder);
+        System.out.println("writing results to: " + benchmarkFolder);
+
+        System.out.println("=== starting " + name);
+        ConsensusRun exp = new ConsensusRun(params, benchmarkFolder, provider.getDataset(params.dataset));
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/consensus/ConsensusParams.java

@@ -0,0 +1,43 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.consensus;
+
+import com.beust.jcommander.Parameter;
+import org.clueminer.clustering.benchmark.AbsParams;
+
+/**
+ *
+ * @author deric
+ */
+public class ConsensusParams extends AbsParams {
+
+    @Parameter(names = "--dataset", description = "use specific dataset")
+    public String dataset = null;
+
+    @Parameter(names = "--algorithm", description = "clustering algorithm name")
+    public String algorithm = "K-Means bagging";
+
+    @Parameter(names = "--k", description = "expected number of clusters (some methods might not respect this)")
+    public int k = -1;
+
+    @Parameter(names = "--method", description = "Initialization and consensus approach")
+    public String method = "";
+
+    @Parameter(names = "--fixed", description = "whether to use 'correct' k as parameter")
+    public boolean fixedK = false;
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/consensus/ConsensusRun.java

@@ -0,0 +1,183 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.consensus;
+
+import com.google.common.base.Supplier;
+import com.google.common.collect.Maps;
+import com.google.common.collect.Table;
+import com.google.common.collect.Tables;
+import java.io.File;
+import java.util.LinkedList;
+import java.util.Map;
+import org.clueminer.bagging.COMUSA;
+import org.clueminer.bagging.CoAssociationReduce;
+import org.clueminer.bagging.KMeansBagging;
+import org.clueminer.clustering.aggl.linkage.AverageLinkage;
+import org.clueminer.clustering.api.AlgParams;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.Clustering;
+import org.clueminer.clustering.api.ClusteringAlgorithm;
+import org.clueminer.clustering.api.ClusteringFactory;
+import org.clueminer.clustering.api.Executor;
+import org.clueminer.clustering.api.factory.EvaluationFactory;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.safeName;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.benchmark.ResultsCollector;
+import org.clueminer.exec.ClusteringExecutorCached;
+import org.clueminer.utils.Props;
+import org.openide.util.Exceptions;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ *
+ * @author deric
+ */
+public class ConsensusRun implements Runnable {
+
+    private static ResultsCollector rc;
+    private ConsensusParams params;
+    private String benchmarkFolder;
+    //table for keeping results from experiments
+    private Table<String, String, Double> table;
+    private static final Logger LOG = LoggerFactory.getLogger(ConsensusRun.class);
+    private Dataset<? extends Instance> dataset;
+
+    public ConsensusRun(ConsensusParams params, String benchmarkFolder, Dataset<? extends Instance> dataset) {
+        this.params = params;
+        this.benchmarkFolder = benchmarkFolder;
+        this.dataset = dataset;
+
+        createTable();
+        rc = new ResultsCollector(table);
+    }
+
+    private void createTable() {
+        table = Tables.newCustomTable(
+                Maps.<String, Map<String, Double>>newHashMap(),
+                new Supplier<Map<String, Double>>() {
+            @Override
+            public Map<String, Double> get() {
+                return Maps.newHashMap();
+            }
+        });
+    }
+
+    @Override
+    public void run() {
+        try {
+            String name;
+            String algorithm;
+            String folder;
+            EvaluationFactory ef = EvaluationFactory.getInstance();
+            LinkedList<ClusterEvaluation> evals = new LinkedList<>();
+            evals.add(ef.getProvider("NMI-sqrt"));
+            evals.add(ef.getProvider("NMI-sum"));
+            evals.add(ef.getProvider("Adjusted Rand"));
+            evals.add(ef.getProvider("Deviation"));
+
+            ClusteringAlgorithm alg = ClusteringFactory.getInstance().getProvider(params.algorithm);
+            algorithm = safeName(alg.getName());
+            Executor exec = new ClusteringExecutorCached(alg);
+
+            createTable();
+            name = safeName(dataset.getName());
+            folder = benchmarkFolder + File.separatorChar + name;
+            ensureFolder(folder);
+
+            String csvRes = folder + File.separatorChar + algorithm + "_" + params.method + "_" + name + ".csv";
+            LOG.info("dataset: {} size: {} num attr: {}", name, dataset.size(), dataset.attributeCount());
+            //ensureFolder(benchmarkFolder + File.separatorChar + name);
+            Clustering c;
+            Props props = algorithmSetup(params.method);
+            if (params.fixedK) {
+                props.putBoolean(KMeansBagging.FIXED_K, true);
+            }
+            if (params.k > 0) {
+                props.putInt("k", params.k);
+            } else if (!props.containsKey("k") && props.getBoolean(KMeansBagging.FIXED_K, false)) {
+                //use "correct" number of clusters if k not specified
+                props.putInt("k", dataset.getClasses().size());
+            }
+            double score;
+            System.out.println(props.toString());
+            for (int i = 0; i < params.repeat; i++) {
+                c = exec.clusterRows(dataset, props);
+                for (ClusterEvaluation eval : evals) {
+                    if (c.getEvaluationTable() != null) {
+                        score = c.getEvaluationTable().getScore(eval);
+                    } else {
+                        score = eval.score(c);
+                    }
+                    System.out.println(eval.getName() + ": " + score + ", clusters: " + c.size());
+                    table.put("run " + i, eval.getName(), score);
+                }
+            }
+            rc.writeAvgColsCsv(table, csvRes);
+
+        } catch (Exception e) {
+            Exceptions.printStackTrace(e);
+        }
+    }
+
+    private Props algorithmSetup(String alg) {
+        Props p = new Props();
+        p.putInt(KMeansBagging.BAGGING, 10);
+        switch (alg) {
+            case "KmB-COMUSA-RAND":
+                p.put(KMeansBagging.CONSENSUS, COMUSA.name);
+                p.put(KMeansBagging.INIT_METHOD, "RANDOM");
+                p.putDouble(COMUSA.RELAX, 1.0);
+                p.putInt(KMeansBagging.MAX_K, 25);
+                break;
+            case "KmB-COMUSA-MO":
+                p.put(KMeansBagging.CONSENSUS, COMUSA.name);
+                p.put(KMeansBagging.INIT_METHOD, "MO");
+                p.putDouble(COMUSA.RELAX, 1.0);
+                p.put("mo_1", "AIC");
+                p.put("mo_2", "SD index");
+                p.putInt(KMeansBagging.MAX_K, 25);
+                break;
+            case "KmB-COMUSA-RAND-fixed":
+                p.put(KMeansBagging.CONSENSUS, COMUSA.name);
+                p.put(KMeansBagging.INIT_METHOD, "RANDOM");
+                p.putDouble(COMUSA.RELAX, 1.0);
+                p.putBoolean(KMeansBagging.FIXED_K, true);
+                break;
+            case "KmB-CoAssocHAC-MO-avg":
+                p.put(KMeansBagging.CONSENSUS, CoAssociationReduce.name);
+                p.put(KMeansBagging.INIT_METHOD, "MO");
+                p.put("mo_1", "AIC");
+                p.put("mo_2", "SD index");
+                p.put(AlgParams.LINKAGE, AverageLinkage.name);
+                break;
+            case "KmB-CoAssocHAC-MO-AIC_SD":
+                p.put(KMeansBagging.CONSENSUS, CoAssociationReduce.name);
+                p.put(KMeansBagging.INIT_METHOD, "MO");
+                p.put("mo_1", "AIC");
+                p.put("mo_2", "SD index");
+                break;
+            default:
+                break;
+
+        }
+        return p;
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/cutoff/CutoffComparison.java

@@ -0,0 +1,245 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.cutoff;
+
+import java.io.File;
+import java.io.PrintWriter;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.LinkedList;
+import java.util.Map;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import org.clueminer.clustering.api.Cluster;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.Clustering;
+import org.clueminer.clustering.api.ClusteringFactory;
+import org.clueminer.clustering.api.CutoffStrategy;
+import org.clueminer.clustering.api.HierarchicalResult;
+import org.clueminer.clustering.api.InternalEvaluator;
+import org.clueminer.clustering.api.ScoreException;
+import org.clueminer.clustering.api.factory.CutoffStrategyFactory;
+import org.clueminer.clustering.api.factory.EvaluationFactory;
+import org.clueminer.clustering.api.factory.InternalEvaluatorFactory;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.safeName;
+import org.clueminer.io.csv.CSVWriter;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.eval.hclust.HillClimbCutoff;
+import org.clueminer.utils.Props;
+import org.openide.util.Exceptions;
+import org.slf4j.LoggerFactory;
+
+/**
+ *
+ * @author Tomas Bruna
+ */
+public class CutoffComparison implements Runnable {
+
+    private final CutoffParams params;
+    private final String benchmarkFolder;
+    private final ArrayList<Dataset<? extends Instance>> datasets;
+    private Map<String, Average> averages;
+    private LinkedList<ClusterEvaluation> externalEvals;
+    private CSVWriter csv;
+    private static final org.slf4j.Logger LOG = LoggerFactory.getLogger(CutoffComparison.class);
+
+    public CutoffComparison(CutoffParams params, String benchmarkFolder, ArrayList<Dataset<? extends Instance>> datasets) {
+        this.params = params;
+        this.benchmarkFolder = benchmarkFolder;
+        this.datasets = datasets;
+        loadExternalEvals();
+    }
+
+    @Override
+    public void run() {
+        try {
+            String folder;
+            AgglomerativeClustering alg = (AgglomerativeClustering) ClusteringFactory.getInstance().getProvider(params.algorithm);
+            folder = benchmarkFolder + File.separatorChar + "Cutoff comparison";
+            ensureFolder(folder);
+            String csvRes = folder + File.separatorChar + "Cutoff comparison with " + safeName(alg.getName()) + " on " + datasets.size() + " datasets.csv";
+
+            PrintWriter writer = new PrintWriter(csvRes, "UTF-8");
+            csv = new CSVWriter(writer, ',');
+            csv.writeLine(alg.getName());
+
+            initAverages();
+            for (Dataset<? extends Instance> dataset : datasets) {
+                System.out.println("Running comparisons on " + dataset.getName());
+                //create dendrogram
+                HierarchicalResult rowsResult = alg.hierarchy(dataset, new Props());
+                writeHeader(dataset);
+
+                String strategies[] = params.strategies.split(",");
+                String internalEvals[] = params.internalEvals.split(",");
+                //try different cutoff methods
+                for (String strategy : strategies) {
+                    for (String internalEval : internalEvals) {
+                        CutoffStrategy cutoff = getCutoffStrategy(strategy.trim(), internalEval.trim());
+                        rowsResult.findCutoff(cutoff);
+                        Clustering c = rowsResult.getClustering();
+
+                        averages.get(strategy.trim() + internalEval.trim()).addValues(c);
+                        writeValues(cutoff, internalEval.trim(), c);
+
+                        if (!(cutoff instanceof HillClimbCutoff) || !(cutoff instanceof HillClimbCutoff)) {
+                            break;
+                        }
+                    }
+                }
+                csv.writeLine("");
+                csv.writeLine("");
+            }
+            writeAverages();
+            csv.close();
+        } catch (Exception e) {
+            Exceptions.printStackTrace(e);
+        }
+    }
+
+    private void loadExternalEvals() {
+        String evals[] = params.externalEvals.split(",");
+        externalEvals = new LinkedList<>();
+        EvaluationFactory ef = EvaluationFactory.getInstance();
+        for (String eval : evals) {
+            externalEvals.add(ef.getProvider(eval.trim()));
+        }
+    }
+
+    private void writeHeader(Dataset<? extends Instance> dataset) {
+        csv.writeLine("Dataset_" + safeName(dataset.getName()));
+        String row[] = new String[externalEvals.size() + 2];
+        row[0] = "Cutoff strategy";
+        row[1] = "Internal eval";
+        int i = 2;
+        for (ClusterEvaluation eval : externalEvals) {
+            row[i] = eval.getName();
+            i++;
+        }
+        csv.writeNext(row);
+    }
+
+    private void writeValues(CutoffStrategy cutoff, String internaEval, Clustering c) {
+        String row[] = new String[externalEvals.size() + 2];
+        row[0] = cutoff.getName();
+        if (cutoff instanceof HillClimbCutoff || cutoff instanceof HillClimbCutoff) {
+            row[1] = internaEval;
+        } else {
+            row[1] = "";
+        }
+        int i = 2;
+        for (ClusterEvaluation eval : externalEvals) {
+            double score;
+            if (c.getEvaluationTable() != null) {
+                score = c.getEvaluationTable().getScore(eval);
+            } else {
+                try {
+                    score = eval.score(c);
+                } catch (ScoreException ex) {
+                    score = Double.NaN;
+                    LOG.info("failed to compute score {}: {}", eval.getName(), ex.getMessage());
+                }
+            }
+            row[i] = String.valueOf(score);
+            i++;
+        }
+        csv.writeNext(row);
+    }
+
+    private void writeAverages() {
+        csv.writeLine("AVERAGES");
+        String row[] = new String[externalEvals.size() + 2];
+        for (Average average : averages.values()) {
+            row[0] = average.name;
+            row[1] = "";
+            int i = 2;
+            for (ClusterEvaluation eval : externalEvals) {
+                row[i] = String.valueOf(average.getAverage(eval.getName()));
+                i++;
+            }
+            csv.writeNext(row);
+        }
+    }
+
+    private CutoffStrategy getCutoffStrategy(String strategy, String eval) {
+        CutoffStrategy cutoffStrategy = CutoffStrategyFactory.getInstance().getProvider(strategy);
+        InternalEvaluatorFactory<Instance, Cluster<Instance>> ief = InternalEvaluatorFactory.getInstance();
+        InternalEvaluator evaluator = ief.getProvider(eval);
+        cutoffStrategy.setEvaluator(evaluator);
+        return cutoffStrategy;
+    }
+
+    private void initAverages() {
+        averages = new HashMap<>();
+        String strategies[] = params.strategies.split(",");
+        String internalEvals[] = params.internalEvals.split(",");
+        for (String strategy : strategies) {
+            for (String internalEval : internalEvals) {
+                CutoffStrategy cutoff = getCutoffStrategy(strategy.trim(), internalEval.trim());
+                if (!(cutoff instanceof HillClimbCutoff) || !(cutoff instanceof HillClimbCutoff)) {
+                    averages.put(strategy.trim() + internalEval.trim(), new Average(strategy.trim()));
+                    break;
+                } else {
+                    averages.put(strategy.trim() + internalEval.trim(), new Average(strategy.trim() + " with " + internalEval.trim()));
+                }
+            }
+        }
+
+    }
+
+    private class Average {
+
+        String name;
+        LinkedList<ClusterEvaluation> evals;
+        Map<String, Double> sum;
+        Map<String, Integer> cnt;
+
+        Average(String name) {
+            this.name = name;
+            sum = new HashMap<>();
+            cnt = new HashMap<>();
+            for (ClusterEvaluation eval : externalEvals) {
+                sum.put(eval.getName(), 0.0);
+                cnt.put(eval.getName(), 0);
+            }
+        }
+
+        public double getAverage(String eval) {
+            return sum.get(eval) / cnt.get(eval);
+        }
+
+        public void addValues(Clustering c) {
+            double score;
+            for (ClusterEvaluation eval : externalEvals) {
+                if (c.getEvaluationTable() != null) {
+                    score = c.getEvaluationTable().getScore(eval);
+                } else {
+                    try {
+                        score = eval.score(c);
+                    } catch (ScoreException ex) {
+                        score = Double.NaN;
+                        LOG.info("failed to compute score {}: {}", eval.getName(), ex.getMessage());
+                    }
+                }
+                sum.put(eval.getName(), sum.get(eval.getName()) + score);
+                cnt.put(eval.getName(), cnt.get(eval.getName()) + 1);
+            }
+        }
+
+    }
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/cutoff/CutoffExp.java

@@ -0,0 +1,85 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.cutoff;
+
+import com.beust.jcommander.JCommander;
+import java.util.ArrayList;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.benchmark.Bench;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.printUsage;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+
+/**
+ *
+ * @author Tomas Bruna
+ */
+public class CutoffExp extends Bench {
+
+    public static final String name = "cutoff";
+
+    protected static CutoffParams parseArguments(String[] args) {
+        CutoffParams params = new CutoffParams();
+        JCommander cmd = new JCommander(params);
+        printUsage(args, cmd, params);
+        return params;
+    }
+
+    @Override
+    public void main(String[] args) {
+        CutoffParams params = parseArguments(args);
+
+        loadBenchArtificial();
+        System.out.println("datasets: " + params.datasets);
+
+        benchmarkFolder = params.home + '/' + "benchmark" + '/' + name;
+        ensureFolder(benchmarkFolder);
+        System.out.println("writing results to: " + benchmarkFolder);
+
+        System.out.println("=== starting " + name);
+        Runnable exp = null;
+        switch (params.mode) {
+            case "comparison": {
+                exp = new CutoffComparison(params, benchmarkFolder, createDatasetsArray(params.datasets));
+                break;
+            }
+            case "firstJump": {
+                exp = new FirstJumpOptimization(params, benchmarkFolder, createDatasetsArray(params.datasets));
+                break;
+            }
+            default: {
+                throw new IllegalArgumentException("Mode " + params.mode + " is not supported");
+            }
+        }
+
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+
+    private ArrayList<Dataset<? extends Instance>> createDatasetsArray(String datasets) {
+        String stringSets[] = datasets.split(",");
+        ArrayList<Dataset<? extends Instance>> sets = new ArrayList<>(stringSets.length);
+        for (String dataset : stringSets) {
+            sets.add(provider.getDataset(dataset.trim()));
+        }
+        return sets;
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/cutoff/CutoffParams.java

@@ -0,0 +1,58 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.cutoff;
+
+import com.beust.jcommander.Parameter;
+import org.clueminer.clustering.benchmark.AbsParams;
+
+/**
+ *
+ * @author Tomas Bruna
+ */
+public class CutoffParams extends AbsParams {
+
+    @Parameter(names = "--datasets", description = "Datasets to test separated by ,")
+    public String datasets = "triangle1, triangle2, flame, jain, long1, long2, long3, sizes1, sizes2, sizes3,"
+            + " sizes4, sizes5, compound, atom, aggregation, lsun, pathbased, smile1, smile2, smile3, twodiamonds, "
+            + "wingnut, target, st900, square1, square2, square3, square4, square5, spiral, spiral2, spherical_6_2, "
+            + "spherical_5_2, longsquare, engytime, donutcurves, diamond9, complex8, complex9, chainlink, R15, D31, "
+            + "2d-4c, 2d-20c-no0, 2d-10c";
+
+    @Parameter(names = "--algorithm", description = "Clustering algorithm name")
+    public String algorithm = "Chameleon";
+
+    @Parameter(names = "--strategy", description = "Cutoff strategies to compare separated by ,")
+    public String strategies = "hill-climb cutoff, hill-climb inc, First jump cutoff";
+
+    @Parameter(names = "--internalEvals", description = "Iternal evaluations to compare separated by ,")
+    public String internalEvals = "Silhouette, SD index";
+
+    @Parameter(names = "--externalEvals", description = "External evaluations to determine quality of results"
+               + " separated by ,")
+    public String externalEvals = "NMI-sqrt, NMI-sum, Deviation, Adjusted Rand";
+
+    @Parameter(names = "--startRange", description = "Range of the start parameter the in the First jump cutoff")
+    public String startRange = "30-400";
+
+    @Parameter(names = "--factorRange", description = "Range of the factor parameter in the First jump cutoff")
+    public String factorRange = "1.01-6";
+
+    @Parameter(names = "--mode", description = "Whether to compare different cutoff methods (option comparison)"
+               + " or to try different parameters for the First jump cutoff (option firstJump)")
+    public String mode = "comparison";
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/cutoff/FirstJumpOptimization.java

@@ -0,0 +1,148 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.cutoff;
+
+import java.io.File;
+import java.io.IOException;
+import java.io.PrintWriter;
+import java.util.ArrayList;
+import java.util.LinkedList;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.Clustering;
+import org.clueminer.clustering.api.ClusteringFactory;
+import org.clueminer.clustering.api.CutoffStrategy;
+import org.clueminer.clustering.api.HierarchicalResult;
+import org.clueminer.clustering.api.ScoreException;
+import org.clueminer.clustering.api.factory.CutoffStrategyFactory;
+import org.clueminer.clustering.api.factory.EvaluationFactory;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.safeName;
+import org.clueminer.io.csv.CSVWriter;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.eval.hclust.FirstJump;
+import org.clueminer.utils.Props;
+import org.openide.util.Exceptions;
+
+/**
+ *
+ * @author Tomas Bruna
+ */
+public class FirstJumpOptimization implements Runnable {
+
+    private final CutoffParams params;
+    private final String benchmarkFolder;
+    private final ArrayList<Dataset<? extends Instance>> datasets;
+    private LinkedList<HierarchicalResult> dendrograms;
+    FirstJump cutoff;
+    ClusterEvaluation eval;
+
+    public FirstJumpOptimization(CutoffParams params, String benchmarkFolder, ArrayList<Dataset<? extends Instance>> datasets) {
+        this.params = params;
+        this.benchmarkFolder = benchmarkFolder;
+        this.datasets = datasets;
+        EvaluationFactory ef = EvaluationFactory.getInstance();
+        eval = ef.getProvider("NMI-sqrt");
+        cutoff = (FirstJump) getCutoffStrategy("First jump cutoff");
+    }
+
+    @Override
+    public void run() {
+        try {
+            String folder;
+            AgglomerativeClustering alg = (AgglomerativeClustering) ClusteringFactory.getInstance().getProvider(params.algorithm);
+            folder = benchmarkFolder + File.separatorChar + "FirstJumpParams";
+            ensureFolder(folder);
+            String csvRes = folder + File.separatorChar + safeName(alg.getName()) + "_" + "FirstJumpParams" + ".csv";
+
+            PrintWriter writer = new PrintWriter(csvRes, "UTF-8");
+            CSVWriter csv = new CSVWriter(writer, ',');
+            csv.writeLine("Clustering_with_" + alg.getName());
+
+            computeDendrograms(alg);
+
+            String startRange[] = params.startRange.split("-");
+            String factorRange[] = params.factorRange.split("-");
+
+            for (int i = Integer.valueOf(startRange[0]); i <= Integer.valueOf(startRange[1]); i += 10) {
+                double j = Double.valueOf(factorRange[0]);
+                while (j <= Double.valueOf(factorRange[1])) {
+                    csv.writeLine("AVERAGE_WITH_" + i + "_AND_" + j + ": " + testParameters(i, j));
+                    j += 0.1;
+                }
+            }
+            csv.close();
+        } catch (NumberFormatException | IOException e) {
+            Exceptions.printStackTrace(e);
+        }
+    }
+
+    /**
+     * Try cutoff with specified parameters on all results
+     *
+     * @param i
+     * @param j
+     * @return
+     */
+    private double testParameters(int i, double j) {
+        System.out.println("Testing " + i + " and " + j);
+        double score;
+        Clustering c;
+        cutoff.setStart(i);
+        cutoff.setFactor(j);
+        double sum = 0;
+        int cnt = 0;
+        //compute cutoff on all results
+        for (HierarchicalResult rowsResult : dendrograms) {
+            rowsResult.findCutoff(cutoff);
+            c = rowsResult.getClustering();
+            if (c.getEvaluationTable() != null) {
+                score = c.getEvaluationTable().getScore(eval);
+            } else {
+                try {
+                    score = eval.score(c);
+                } catch (ScoreException ex) {
+                    score = Double.NaN;
+                    Exceptions.printStackTrace(ex);
+                }
+            }
+            sum += score;
+            cnt++;
+        }
+        return sum / cnt;
+    }
+
+    /**
+     * Cluster all datasets and save results
+     *
+     * @param alg
+     */
+    private void computeDendrograms(AgglomerativeClustering alg) {
+        dendrograms = new LinkedList<>();
+        for (Dataset<? extends Instance> dataset : datasets) {
+            HierarchicalResult rowsResult = alg.hierarchy(dataset, new Props());
+            dendrograms.add(rowsResult);
+        }
+    }
+
+    private CutoffStrategy getCutoffStrategy(String strategy) {
+        CutoffStrategy cutoffStrategy = CutoffStrategyFactory.getInstance().getProvider(strategy);
+        return cutoffStrategy;
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/evolve/EvolveExp.java

@@ -0,0 +1,117 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.evolve;
+
+import com.google.common.base.Supplier;
+import com.google.common.collect.Maps;
+import com.google.common.collect.Table;
+import com.google.common.collect.Tables;
+import java.io.File;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.Map.Entry;
+import org.clueminer.clustering.api.AlgParams;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.factory.ExternalEvaluatorFactory;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.safeName;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.benchmark.GnuplotWriter;
+import org.clueminer.dataset.benchmark.ResultsCollector;
+import org.clueminer.evolution.multim.MultiMuteEvolution;
+import org.clueminer.evolution.utils.ConsoleDump;
+import org.openide.util.Exceptions;
+
+/**
+ * Evolution of hierarchical clusterings with different (unsupervised)
+ * optimization criterion (single criterion)
+ *
+ * @author Tomas Barton
+ */
+public class EvolveExp implements Runnable {
+
+    private static ResultsCollector rc;
+    private EvolveParams params;
+    private String benchmarkFolder;
+    private ClusterEvaluation[] scores;
+    private HashMap<String, Entry<Dataset<? extends Instance>, Integer>> datasets;
+    //table for keeping results from experiments
+    private final Table<String, String, Double> table;
+
+    public EvolveExp(EvolveParams params, String benchmarkFolder, ClusterEvaluation[] scores, HashMap<String, Entry<Dataset<? extends Instance>, Integer>> availableDatasets) {
+        this.params = params;
+        this.benchmarkFolder = benchmarkFolder;
+        this.scores = scores;
+        this.datasets = availableDatasets;
+
+        table = Tables.newCustomTable(
+                Maps.<String, Map<String, Double>>newHashMap(),
+                new Supplier<Map<String, Double>>() {
+            @Override
+            public Map<String, Double> get() {
+                return Maps.newHashMap();
+            }
+        });
+        rc = new ResultsCollector(table);
+    }
+
+    @Override
+    public void run() {
+        try {
+            MultiMuteEvolution evolution;
+            String name;
+
+            ClusterEvaluation ext = fetchExternal(params.external);
+            //evolution.setAlgorithm(new HACLW());
+            System.out.println("datasets size: " + datasets.size());
+            for (Map.Entry<String, Map.Entry<Dataset<? extends Instance>, Integer>> e : datasets.entrySet()) {
+                Dataset<? extends Instance> d = e.getValue().getKey();
+                name = safeName(d.getName());
+                String csvRes = benchmarkFolder + File.separatorChar + name + File.separatorChar + name + ".csv";
+                System.out.println("=== dataset " + name);
+                System.out.println("size: " + d.size());
+                ensureFolder(benchmarkFolder + File.separatorChar + name);
+                for (ClusterEvaluation eval : scores) {
+                    evolution = new MultiMuteEvolution();
+                    evolution.setDataset(d);
+                    evolution.setEvaluator(eval);
+                    evolution.setExternal(ext);
+                    evolution.setGenerations(params.generations);
+                    evolution.setPopulationSize(params.population);
+                    GnuplotWriter gw = new GnuplotWriter(evolution, benchmarkFolder, name + File.separatorChar + safeName(eval.getName()));
+                    gw.setPlotDumpMod(50);
+                    gw.setCustomTitle("cutoff=" + evolution.getDefaultParam(AlgParams.CUTOFF_STRATEGY) + "(" + evolution.getDefaultParam(AlgParams.CUTOFF_SCORE) + ")");
+                    //collect data from evolution
+                    evolution.addEvolutionListener(new ConsoleDump());
+                    evolution.addEvolutionListener(gw);
+                    evolution.addEvolutionListener(rc);
+                    evolution.run();
+                    System.out.println("## updating results in: " + csvRes);
+                    rc.writeToCsv(csvRes);
+                }
+            }
+        } catch (Exception e) {
+            Exceptions.printStackTrace(e);
+        }
+    }
+
+    private ClusterEvaluation fetchExternal(String external) {
+        return ExternalEvaluatorFactory.getInstance().getProvider(external);
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/evolve/EvolveParams.java

@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.evolve;
+
+import com.beust.jcommander.Parameter;
+import org.clueminer.clustering.benchmark.AbsParams;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class EvolveParams extends AbsParams {
+
+    @Parameter(names = "--external", description = "reference criterion for comparing with internal criterion (Precision, Accuracy, NMI)")
+    public String external = "AUC";
+
+    @Parameter(names = "--test", description = "test only on one dataset")
+    public boolean test = false;
+
+    @Parameter(names = "--generations", description = "number of generations in evolution")
+    public int generations = 10;
+
+    @Parameter(names = "--population", description = "size of population in each generation")
+    public int population = 10;
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/exp/Data.java

@@ -0,0 +1,188 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.exp;
+
+import com.google.common.base.Supplier;
+import com.google.common.collect.Maps;
+import com.google.common.collect.Table;
+import com.google.common.collect.Tables;
+import java.io.File;
+import java.util.HashMap;
+import java.util.Map;
+import org.clueminer.clustering.algorithm.KMeans;
+import org.clueminer.clustering.api.Cluster;
+import org.clueminer.clustering.api.ExternalEvaluator;
+import org.clueminer.clustering.api.InternalEvaluator;
+import org.clueminer.clustering.api.factory.InternalEvaluatorFactory;
+import org.clueminer.clustering.benchmark.Bench;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.benchmark.GnuplotWriter;
+import org.clueminer.dataset.benchmark.ResultsCollector;
+import org.clueminer.eval.external.JaccardIndex;
+import org.clueminer.evolution.attr.AttrEvolution;
+import org.clueminer.evolution.utils.ConsoleDump;
+import org.clueminer.utils.FileUtils;
+import org.openide.util.NbBundle;
+
+/**
+ *
+ * @author tombart
+ */
+public class Data extends Bench {
+
+    private AttrEvolution test;
+    //table for keeping results from experiments
+    private Table<String, String, Double> table;
+    private static ResultsCollector rc;
+    private static String csvOutput;
+    private static Data instance;
+
+    /**
+     * @param args the command line arguments
+     */
+    @Override
+    public void main(String[] args) {
+        int i = 0, j;
+        String arg;
+        char flag;
+        boolean vflag = false;
+        String datasetName = "";
+
+        while (i < args.length && args[i].startsWith("-")) {
+            arg = args[i++];
+
+            // use this type of check for "wordy" arguments
+            switch (arg) {
+                // use this type of check for arguments that require arguments
+                case "-verbose":
+                    System.out.println("verbose mode on");
+                    vflag = true;
+                    break;
+                // use this type of check for a series of flag arguments
+                case "-dataset":
+                    if (i < args.length) {
+                        datasetName = args[i++];
+                    } else {
+                        System.err.println("-dataset requires a name");
+                    }
+                    if (vflag) {
+                        System.out.println("dataset = " + datasetName);
+                    }
+                    break;
+                default:
+                    for (j = 1; j < arg.length(); j++) {
+                        flag = arg.charAt(j);
+                        switch (flag) {
+                            case 'x':
+                                if (vflag) {
+                                    System.out.println("Option x");
+                                }
+                                break;
+                            case 'n':
+                                if (vflag) {
+                                    System.out.println("Option n");
+                                }
+                                break;
+                            default:
+                                System.err.println("Run: illegal option " + flag);
+                                break;
+                        }
+                    }
+                    break;
+            }
+        }
+        if (i == args.length) {
+            System.err.println("Usage: Benchmark [-verbose] [-xn] [-dataset name]");
+        }
+
+        init();
+        execute(datasetName);
+    }
+
+    private void init() {
+        table = Tables.newCustomTable(
+                Maps.<String, Map<String, Double>>newHashMap(),
+                new Supplier<Map<String, Double>>() {
+            @Override
+            public Map<String, Double> get() {
+                return Maps.newHashMap();
+            }
+        });
+
+        String home = System.getProperty("user.home") + File.separatorChar
+                + NbBundle.getMessage(
+                        FileUtils.class,
+                        "FOLDER_Home");
+        ensureFolder(home);
+        benchmarkFolder = home + File.separatorChar + "benchmark";
+        ensureFolder(benchmarkFolder);
+        rc = new ResultsCollector(table);
+        csvOutput = benchmarkFolder + File.separatorChar + "results.csv";
+
+        //preload dataset names
+        loadDatasets();
+    }
+
+    public void execute(String datasetName) {
+        Map<Dataset<? extends Instance>, Integer> datasets = new HashMap<>();
+        if (availableDatasets.containsKey(datasetName)) {
+            Map.Entry<Dataset<? extends Instance>, Integer> entry = availableDatasets.get(datasetName);
+            datasets.put(entry.getKey(), entry.getValue());
+        } else {
+            System.out.println("dataset " + datasetName + " not found");
+            System.out.println("known datasets: ");
+            for (String d : availableDatasets.keySet()) {
+                System.out.print(d + " ");
+            }
+            System.out.println("---");
+        }
+        // DatasetFixture.allDatasets();
+
+        InternalEvaluatorFactory<Instance, Cluster<Instance>> factory = InternalEvaluatorFactory.getInstance();
+        ExternalEvaluator ext = new JaccardIndex();
+
+        String name;
+        System.out.println("working folder: " + benchmarkFolder);
+        for (Map.Entry<Dataset<? extends Instance>, Integer> entry : datasets.entrySet()) {
+            Dataset<? extends Instance> dataset = entry.getKey();
+            name = dataset.getName();
+            String csvRes = benchmarkFolder + File.separatorChar + name + File.separatorChar + name + ".csv";
+            System.out.println("=== dataset " + name);
+            System.out.println("size: " + dataset.size());
+            System.out.println(dataset.toString());
+            String dataDir = benchmarkFolder + File.separatorChar + name;
+            (new File(dataDir)).mkdir();
+            for (InternalEvaluator eval : factory.getAll()) {
+                System.out.println("evaluator: " + eval.getName());
+                test = new AttrEvolution(dataset, 20);
+                test.setAlgorithm(new KMeans());
+                test.setK(entry.getValue());
+                test.setEvaluator(eval);
+                test.setExternal(ext);
+                GnuplotWriter gw = new GnuplotWriter(test, benchmarkFolder, name + "/" + name + "-" + safeName(eval.getName()));
+                gw.setPlotDumpMod(50);
+                //collect data from evolution
+                test.addEvolutionListener(new ConsoleDump());
+                test.addEvolutionListener(gw);
+                test.addEvolutionListener(rc);
+                test.run();
+                rc.writeToCsv(csvRes);
+            }
+        }
+    }
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/exp/EvolveScores.java

@@ -0,0 +1,78 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.exp;
+
+import com.beust.jcommander.JCommander;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.InternalEvaluator;
+import org.clueminer.clustering.api.factory.InternalEvaluatorFactory;
+import org.clueminer.clustering.benchmark.Bench;
+import org.clueminer.clustering.benchmark.evolve.EvolveExp;
+import org.clueminer.clustering.benchmark.evolve.EvolveParams;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.log.ClmLog;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class EvolveScores extends Bench {
+
+    public static final String name = "evolve-sc";
+
+    protected static EvolveParams parseArguments(String[] args) {
+        EvolveParams params = new EvolveParams();
+        JCommander cmd = new JCommander(params);
+        printUsage(args, cmd, params);
+        return params;
+    }
+
+    @Override
+    public void main(String[] args) {
+        EvolveParams params = parseArguments(args);
+        if (params.test) {
+            load("iris");
+        } else {
+            loadDatasets();
+        }
+        ClmLog.setup(params.log);
+        System.out.println("loaded dataset");
+        int i = 0;
+        for (Map.Entry<String, Map.Entry<Dataset<? extends Instance>, Integer>> e : availableDatasets.entrySet()) {
+            System.out.println((i++) + ":" + e.getKey());
+        }
+
+        benchmarkFolder = params.home + '/' + "benchmark" + '/' + name;
+        ensureFolder(benchmarkFolder);
+        System.out.println("writing results to: " + benchmarkFolder);
+
+        System.out.println("=== starting " + name);
+        List<InternalEvaluator> eval = InternalEvaluatorFactory.getInstance().getAll();
+        ClusterEvaluation[] scores = eval.toArray(new ClusterEvaluation[eval.size()]);
+        System.out.println("scores size: " + scores.length);
+        EvolveExp exp = new EvolveExp(params, benchmarkFolder, scores, availableDatasets);
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/exp/HclusPar.java

@@ -0,0 +1,59 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.exp;
+
+import java.io.File;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.aggl.HCLW;
+import org.clueminer.clustering.aggl.HCLWMS;
+import org.clueminer.clustering.aggl.HacLwMsPar;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import org.clueminer.clustering.benchmark.BenchParams;
+import org.clueminer.clustering.benchmark.Experiment;
+import org.clueminer.log.ClmLog;
+
+/**
+ *
+ * @author deric
+ */
+public class HclusPar extends Hclust {
+
+    /**
+     * @param args the command line arguments
+     */
+    @Override
+    public void main(String[] args) {
+        BenchParams params = parseArguments(args);
+        ClmLog.setup(params.log);
+
+        benchmarkFolder = params.home + File.separatorChar + "benchmark" + File.separatorChar + "hclust-par";
+        ensureFolder(benchmarkFolder);
+
+        System.out.println("# n = " + params.n);
+        System.out.println("=== starting experiment:");
+        AgglomerativeClustering[] algorithms = new AgglomerativeClustering[]{
+            new HCLW(), new HCLWMS(), new HacLwMsPar(4), new HacLwMsPar(8), new HacLwMsPar(16), new HacLwMsPar(32)
+        };
+        Experiment exp = new Experiment(params, benchmarkFolder, algorithms);
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/exp/HclusPar2.java

@@ -0,0 +1,60 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.exp;
+
+import java.io.File;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.aggl.HCLW;
+import org.clueminer.clustering.aggl.HCLWMS;
+import org.clueminer.clustering.aggl.HacLwMsPar;
+import org.clueminer.clustering.aggl.HacLwMsPar2;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import org.clueminer.clustering.benchmark.BenchParams;
+import org.clueminer.clustering.benchmark.Experiment;
+import static org.clueminer.clustering.benchmark.exp.Hclust.parseArguments;
+import org.clueminer.log.ClmLog;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class HclusPar2 extends Hclust {
+
+    /**
+     * @param args the command line arguments
+     */
+    @Override
+    public void main(String[] args) {
+        BenchParams params = parseArguments(args);
+        ClmLog.setup(params.log);
+
+        benchmarkFolder = params.home + File.separatorChar + "hclust-par2";
+        ensureFolder(benchmarkFolder);
+
+        System.out.println("# n = " + params.n);
+        System.out.println("=== starting experiment:");
+        AgglomerativeClustering[] algorithms = new AgglomerativeClustering[]{
+            new HCLW(), new HCLWMS(), new HacLwMsPar(2), new HacLwMsPar(4), new HacLwMsPar2(2), new HacLwMsPar2(4)
+        };
+        Experiment exp = new Experiment(params, benchmarkFolder, algorithms);
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/exp/Hclust.java

@@ -0,0 +1,100 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.exp;
+
+import com.beust.jcommander.JCommander;
+import com.beust.jcommander.ParameterException;
+import java.io.File;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.aggl.HC;
+import org.clueminer.clustering.aggl.HCLW;
+import org.clueminer.clustering.aggl.HCLWMS;
+import org.clueminer.clustering.api.AgglomerativeClustering;
+import org.clueminer.clustering.benchmark.Bench;
+import org.clueminer.clustering.benchmark.BenchParams;
+import org.clueminer.clustering.benchmark.Experiment;
+import org.clueminer.log.ClmLog;
+
+/**
+ *
+ * @author deric
+ */
+public class Hclust extends Bench {
+
+    protected static Hclust instance;
+
+    /**
+     * @param args the command line arguments
+     */
+    @Override
+    public void main(String[] args) {
+        BenchParams params = parseArguments(args);
+        ClmLog.setup(params.log);
+
+        benchmarkFolder = params.home + File.separatorChar + "benchmark" + File.separatorChar + "hclust";
+        ensureFolder(benchmarkFolder);
+
+        System.out.println("# n = " + params.n);
+        System.out.println("=== starting experiment:");
+        AgglomerativeClustering[] algorithms = new AgglomerativeClustering[]{new HC(), new HCLW(), new HCLWMS()};
+        Experiment exp = new Experiment(params, benchmarkFolder, algorithms);
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+
+    protected static BenchParams parseArguments(String[] args) {
+        BenchParams params = new BenchParams();
+        JCommander cmd = new JCommander(params);
+        printUsage(args, cmd, params);
+        return params;
+    }
+
+    public static void printUsage(String[] args, JCommander cmd, BenchParams params) {
+        /* if (args.length == 0) { StringBuilder sb = new StringBuilder();
+         * cmd.usage(sb);
+         * sb.append("\n").append("attributes marked with * are mandatory");
+         * System.out.println(sb);
+         * System.err.println("missing mandatory arguments");
+         * System.exit(0);
+         * } */
+        try {
+            cmd.parse(args);
+            /**
+             * TODO validate values of parameters
+             */
+            if (params.n <= 0 || params.dimension <= 0) {
+                throw new ParameterException("invalid data dimensions " + params.n + " x " + params.dimension);
+            }
+
+            if (params.steps <= 0) {
+                throw new ParameterException("invalid steps size " + params.steps);
+            }
+
+            if (params.nSmall == params.n) {
+                throw new ParameterException("n can't be same as n-small! " + params.nSmall);
+            }
+
+        } catch (ParameterException ex) {
+            System.out.println(ex.getMessage());
+            cmd.usage();
+            System.exit(0);
+        }
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/gen/NsgaGen.java

@@ -0,0 +1,76 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.gen;
+
+import com.beust.jcommander.JCommander;
+import java.util.Map;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.api.Cluster;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.factory.InternalEvaluatorFactory;
+import org.clueminer.clustering.benchmark.Bench;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.printUsage;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.log.ClmLog;
+
+/**
+ *
+ * @author deric
+ */
+public class NsgaGen extends Bench {
+
+    public static final String name = "nsga-gen";
+
+    protected static NsgaGenParams parseArguments(String[] args) {
+        NsgaGenParams params = new NsgaGenParams();
+        JCommander cmd = new JCommander(params);
+        printUsage(args, cmd, params);
+        return params;
+    }
+
+    @Override
+    public void main(String[] args) {
+        NsgaGenParams params = parseArguments(args);
+        if (params.dataset != null) {
+            load(params.dataset);
+        } else {
+            loadDatasets();
+        }
+        ClmLog.setup(params.log);
+
+        int i = 0;
+        for (Map.Entry<String, Map.Entry<Dataset<? extends Instance>, Integer>> e : availableDatasets.entrySet()) {
+            System.out.println((i++) + ":" + e.getKey());
+        }
+
+        benchmarkFolder = params.home + '/' + "benchmark" + '/' + name;
+        ensureFolder(benchmarkFolder);
+        System.out.println("writing results to: " + benchmarkFolder);
+
+        System.out.println("=== starting " + name);
+        InternalEvaluatorFactory<Instance, Cluster<Instance>> factory = InternalEvaluatorFactory.getInstance();
+        ClusterEvaluation c1 = factory.getProvider(params.c1);
+        ClusterEvaluation c2 = factory.getProvider(params.c2);
+        NsgaGenExp exp = new NsgaGenExp(params, benchmarkFolder, c1, c2, availableDatasets);
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/gen/NsgaGenExp.java

@@ -0,0 +1,131 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.gen;
+
+import com.google.common.base.Supplier;
+import com.google.common.collect.Maps;
+import com.google.common.collect.Table;
+import com.google.common.collect.Tables;
+import java.io.File;
+import java.util.HashMap;
+import java.util.Map;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.factory.EvaluationFactory;
+import static org.clueminer.clustering.benchmark.Bench.safeName;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.benchmark.GnuplotMO;
+import org.clueminer.dataset.benchmark.ResultsCollector;
+import org.clueminer.evolution.mo.MoEvolution;
+import org.clueminer.evolution.utils.ConsoleDump;
+import org.openide.util.Exceptions;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ *
+ * @author deric
+ */
+public class NsgaGenExp implements Runnable {
+
+    private static ResultsCollector rc;
+    private NsgaGenParams params;
+    private String benchmarkFolder;
+    private HashMap<String, Map.Entry<Dataset<? extends Instance>, Integer>> datasets;
+    //table for keeping results from experiments
+    private Table<String, String, Double> table;
+    private ClusterEvaluation c1;
+    private ClusterEvaluation c2;
+    private static final Logger LOG = LoggerFactory.getLogger(NsgaGenExp.class);
+
+    public NsgaGenExp(NsgaGenParams params, String benchmarkFolder, ClusterEvaluation c1, ClusterEvaluation c2, HashMap<String, Map.Entry<Dataset<? extends Instance>, Integer>> availableDatasets) {
+        this.params = params;
+        this.benchmarkFolder = benchmarkFolder;
+        this.c1 = c1;
+        this.c2 = c2;
+        this.datasets = availableDatasets;
+
+        createTable();
+        rc = new ResultsCollector(table);
+    }
+
+    private void createTable() {
+        table = Tables.newCustomTable(
+                Maps.<String, Map<String, Double>>newHashMap(),
+                new Supplier<Map<String, Double>>() {
+            @Override
+            public Map<String, Double> get() {
+                return Maps.newHashMap();
+            }
+        });
+    }
+
+    @Override
+    public void run() {
+        try {
+            MoEvolution evolution = new MoEvolution();
+
+            evolution.setPopulationSize(params.population);
+            evolution.setNumSolutions(params.solutions);
+            evolution.setExternal(EvaluationFactory.getInstance().getProvider("Jaccard"));
+            evolution.setMutationProbability(params.mutation);
+            evolution.setCrossoverProbability(params.crossover);
+
+            GnuplotMO gw = new GnuplotMO();
+            //gw.setCustomTitle("cutoff=" + evolution.getDefaultParam(AgglParams.CUTOFF_STRATEGY) + "(" + evolution.getDefaultParam(AgglParams.CUTOFF_SCORE) + ")");
+            //collect data from evolution
+            evolution.addEvolutionListener(new ConsoleDump());
+            evolution.addMOEvolutionListener(gw);
+            evolution.addMOEvolutionListener(rc);
+            evolution.addObjective(c1);
+            evolution.addObjective(c2);
+
+            int[] generations = new int[]{1, 10, 50, 100, 1000};
+
+            String name;
+            String folder;
+            LOG.info("datasets size: {}", datasets.size());
+            for (Map.Entry<String, Map.Entry<Dataset<? extends Instance>, Integer>> e : datasets.entrySet()) {
+                Dataset<? extends Instance> d = e.getValue().getKey();
+                name = safeName(d.getName());
+                folder = benchmarkFolder + File.separatorChar + name;
+                gw.mkdir(folder);
+                String csvRes = folder + File.separatorChar + "_" + name + ".csv";
+                LOG.info("dataset: {} size: {} num attr: {}", name, d.size(), d.attributeCount());
+                //ensureFolder(benchmarkFolder + File.separatorChar + name);
+
+                evolution.setDataset(d);
+
+                for (int i = 0; i < generations.length; i++) {
+                    int g = generations[i];
+                    evolution.setGenerations(g);
+                    gw.setCurrentDir(benchmarkFolder, name + "-" + g);
+                    //for (int k = 0; k < params.repeat; k++) {
+                    //   logger.log(Level.INFO, "run {0}: {1} & {2}", new Object[]{k, c1.getName(), c2.getName()});
+                    evolution.run();
+                    rc.writeToCsv(csvRes);
+                    //}
+                    evolution.fireFinishedBatch();
+                }
+                createTable();
+            }
+        } catch (Exception e) {
+            Exceptions.printStackTrace(e);
+        }
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/gen/NsgaGenParams.java

@@ -0,0 +1,49 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.gen;
+
+import com.beust.jcommander.Parameter;
+import org.clueminer.clustering.benchmark.AbsParams;
+
+/**
+ *
+ * @author deric
+ */
+public class NsgaGenParams extends AbsParams {
+
+    @Parameter(names = "--population", description = "size of population in each generation")
+    public int population = 20;
+
+    @Parameter(names = "--solutions", description = "number of final solutions which will be returned as result")
+    public int solutions = 10;
+
+    @Parameter(names = "--mutation", description = "probability of mutation")
+    public double mutation = 0.5;
+
+    @Parameter(names = "--crossover", description = "probability of crossover")
+    public double crossover = 0.5;
+
+    @Parameter(names = "--dataset", description = "use specific dataset")
+    public String dataset = null;
+
+    @Parameter(names = "--c1", description = "criterion 1")
+    public String c1 = "Davies-Bouldin";
+
+    @Parameter(names = "--c2", description = "criterion 2")
+    public String c2 = "AIC";
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/nsga/NsgaExp.java

@@ -0,0 +1,134 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.nsga;
+
+import com.google.common.base.Supplier;
+import com.google.common.collect.Maps;
+import com.google.common.collect.Table;
+import com.google.common.collect.Tables;
+import java.io.File;
+import java.util.HashMap;
+import java.util.Map;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.factory.EvaluationFactory;
+import static org.clueminer.clustering.benchmark.Bench.safeName;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.benchmark.GnuplotMO;
+import org.clueminer.dataset.benchmark.ResultsCollector;
+import org.clueminer.evolution.mo.MoEvolution;
+import org.clueminer.evolution.utils.ConsoleDump;
+import org.openide.util.Exceptions;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class NsgaExp implements Runnable {
+
+    private static ResultsCollector rc;
+    private NsgaParams params;
+    private String benchmarkFolder;
+    private ClusterEvaluation[] scores;
+    private HashMap<String, Map.Entry<Dataset<? extends Instance>, Integer>> datasets;
+    //table for keeping results from experiments
+    private Table<String, String, Double> table;
+    private static final Logger LOG = LoggerFactory.getLogger(NsgaExp.class);
+
+    public NsgaExp(NsgaParams params, String benchmarkFolder, ClusterEvaluation[] scores, HashMap<String, Map.Entry<Dataset<? extends Instance>, Integer>> availableDatasets) {
+        this.params = params;
+        this.benchmarkFolder = benchmarkFolder;
+        this.scores = scores;
+        this.datasets = availableDatasets;
+
+        createTable();
+        rc = new ResultsCollector(table);
+    }
+
+    @Override
+    public void run() {
+        try {
+            MoEvolution evolution = new MoEvolution();
+            evolution.setGenerations(params.generations);
+            evolution.setPopulationSize(params.population);
+            evolution.setNumSolutions(params.solutions);
+            evolution.setExternal(EvaluationFactory.getInstance().getProvider(params.supervised));
+            evolution.setMutationProbability(params.mutation);
+            evolution.setCrossoverProbability(params.crossover);
+            evolution.setkLimit(params.limitK);
+            ClusterEvaluation c1, c2;
+
+            GnuplotMO gw = new GnuplotMO();
+            //gw.setCustomTitle("cutoff=" + evolution.getDefaultParam(AgglParams.CUTOFF_STRATEGY) + "(" + evolution.getDefaultParam(AgglParams.CUTOFF_SCORE) + ")");
+            //collect data from evolution
+            evolution.addEvolutionListener(new ConsoleDump());
+            evolution.addMOEvolutionListener(gw);
+            evolution.addMOEvolutionListener(rc);
+
+            String name;
+            LOG.info("datasets size: {}", datasets.size());
+            for (Map.Entry<String, Map.Entry<Dataset<? extends Instance>, Integer>> e : datasets.entrySet()) {
+                Dataset<? extends Instance> d = e.getValue().getKey();
+                name = safeName(d.getName());
+                String csvRes = benchmarkFolder + File.separatorChar + name + File.separatorChar + "_" + name + ".csv";
+                LOG.info("dataset: {} size: {} num attr: {}", name, d.size(), d.attributeCount());
+                //ensureFolder(benchmarkFolder + File.separatorChar + name);
+
+                gw.setCurrentDir(benchmarkFolder, name);
+
+                evolution.setDataset(d);
+
+                for (int i = 0; i < scores.length; i++) {
+                    c1 = scores[i];
+                    //lower triangular matrix without diagonal
+                    //(doesn't matter which criterion is first, we want to try
+                    //all combinations)
+                    for (int j = 0; j < i; j++) {
+                        c2 = scores[j];
+                        evolution.clearObjectives();
+                        evolution.addObjective(c1);
+                        evolution.addObjective(c2);
+                        //run!
+                        for (int k = 0; k < params.repeat; k++) {
+                            LOG.info("run {}: {} & {}", k, c1.getName(), c2.getName());
+                            evolution.run();
+                            rc.writeToCsv(csvRes);
+                        }
+                        evolution.fireFinishedBatch();
+                        LOG.info("finished {} & {}", c1.getName(), c2.getName());
+                    }
+                }
+                createTable();
+            }
+        } catch (Exception e) {
+            Exceptions.printStackTrace(e);
+        }
+    }
+
+    private void createTable() {
+        table = Tables.newCustomTable(
+                Maps.<String, Map<String, Double>>newHashMap(),
+                new Supplier<Map<String, Double>>() {
+            @Override
+            public Map<String, Double> get() {
+                return Maps.newHashMap();
+            }
+        });
+    }
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/nsga/NsgaParams.java

@@ -0,0 +1,55 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.nsga;
+
+import com.beust.jcommander.Parameter;
+import org.clueminer.clustering.benchmark.AbsParams;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class NsgaParams extends AbsParams {
+
+    @Parameter(names = "--test", description = "test only on one dataset")
+    public boolean test = false;
+
+    @Parameter(names = "--generations", description = "number of generations in evolution")
+    public int generations = 10;
+
+    @Parameter(names = "--population", description = "size of population in each generation")
+    public int population = 20;
+
+    @Parameter(names = "--solutions", description = "number of final solutions which will be returned as result")
+    public int solutions = 10;
+
+    @Parameter(names = "--supervised", description = "supervised criterion for external evaluation")
+    public String supervised = "Adjusted Rand";
+
+    @Parameter(names = "--mutation", description = "probability of mutation")
+    public double mutation = 0.5;
+
+    @Parameter(names = "--crossover", description = "probability of crossover")
+    public double crossover = 0.5;
+
+    @Parameter(names = "--dataset", description = "use specific dataset")
+    public String dataset = null;
+
+    @Parameter(names = "--limit-k", description = "limit max. clusterings size to sqrt(n)")
+    public boolean limitK = false;
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/nsga/NsgaScore.java

@@ -0,0 +1,82 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.nsga;
+
+import com.beust.jcommander.JCommander;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.api.ClusterEvaluation;
+import org.clueminer.clustering.api.InternalEvaluator;
+import org.clueminer.clustering.api.factory.InternalEvaluatorFactory;
+import org.clueminer.clustering.benchmark.Bench;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.printUsage;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.log.ClmLog;
+
+/**
+ *
+ * @author Tomas Barton
+ */
+public class NsgaScore extends Bench {
+
+    public static final String name = "nsga-scores";
+
+    protected static NsgaParams parseArguments(String[] args) {
+        NsgaParams params = new NsgaParams();
+        JCommander cmd = new JCommander(params);
+        printUsage(args, cmd, params);
+        return params;
+    }
+
+    @Override
+    public void main(String[] args) {
+        NsgaParams params = parseArguments(args);
+        if (params.test || params.dataset != null) {
+            if (params.test) {
+                load("iris");
+            } else {
+                load(params.dataset);
+            }
+        } else {
+            loadDatasets();
+        }
+        System.out.println("loaded dataset");
+        ClmLog.setup(params.log);
+
+        int i = 0;
+        for (Map.Entry<String, Map.Entry<Dataset<? extends Instance>, Integer>> e : availableDatasets.entrySet()) {
+            System.out.println((i++) + ":" + e.getKey());
+        }
+
+        benchmarkFolder = params.home + '/' + "benchmark" + '/' + name;
+        ensureFolder(benchmarkFolder);
+        System.out.println("writing results to: " + benchmarkFolder);
+
+        System.out.println("=== starting " + name);
+        List<InternalEvaluator> eval = InternalEvaluatorFactory.getInstance().getAll();
+        ClusterEvaluation[] scores = eval.toArray(new ClusterEvaluation[eval.size()]);
+        System.out.println("scores size: " + scores.length);
+        NsgaExp exp = new NsgaExp(params, benchmarkFolder, scores, availableDatasets);
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/partition/PartitionBench.java

@@ -0,0 +1,151 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.partition;
+
+import java.util.Random;
+import static org.clueminer.chameleon.Chameleon.K;
+import static org.clueminer.chameleon.Chameleon.MAX_PARTITION;
+import org.clueminer.clustering.benchmark.GnuplotReporter;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.impl.ArrayDataset;
+import org.clueminer.graph.adjacencyMatrix.AdjMatrixGraph;
+import org.clueminer.graph.api.Graph;
+import org.clueminer.graph.knn.KNNGraphBuilder;
+import org.clueminer.partitioning.api.Partitioning;
+import org.clueminer.report.NanoBench;
+import org.clueminer.utils.Props;
+import org.openide.util.Exceptions;
+
+/**
+ *
+ * @author deric
+ */
+public class PartitionBench implements Runnable {
+
+    protected final Random rand;
+    protected final PartitionParams params;
+    protected final Partitioning[] algorithms;
+    protected final String results;
+
+    public PartitionBench(PartitionParams params, String results, Partitioning[] algorithms) {
+        rand = new Random();
+        this.params = params;
+        this.results = results;
+        this.algorithms = algorithms;
+    }
+
+    @Override
+    public void run() {
+        int inc = (params.n - params.nSmall) / params.steps;
+
+        String[] names = new String[algorithms.length];
+        int j = 0;
+        for (Partitioning alg : algorithms) {
+            names[j++] = alg.getName();
+        }
+
+        GnuplotReporter reporter = new GnuplotReporter(results,
+                new String[]{"algorithm", "edges", "n"}, names, params.nSmall + "-" + params.n, 10);
+        System.out.println("increment = " + inc);
+        KNNGraphBuilder knn = new KNNGraphBuilder();
+        Props pref = new Props();
+        for (int i = params.nSmall; i <= params.n; i += inc) {
+            Graph g = new AdjMatrixGraph(i);
+            Dataset<? extends Instance> dataset = generateData(i, params.dimension);
+            int datasetK = determineK(dataset);
+            int maxPartitionSize = determineMaxPartitionSize(dataset);
+            pref.putInt(MAX_PARTITION, maxPartitionSize);
+            pref.putInt(K, datasetK);
+            g = knn.getNeighborGraph(dataset, g, datasetK);
+
+            for (Partitioning alg : algorithms) {
+                String[] opts = new String[]{alg.getName(), String.valueOf(g.getEdgeCount()), String.valueOf(dataset.size())};
+                NanoBench.create().measurements(params.repeat).collect(reporter, opts).measure(
+                        alg.getName() + " - " + dataset.size(),
+                        bench(alg, g, maxPartitionSize, pref)
+                );
+                // Get the Java runtime
+                Runtime runtime = Runtime.getRuntime();
+                // Run the garbage collector
+                runtime.gc();
+                try {
+                    Thread.sleep(1000);
+                } catch (InterruptedException ex) {
+                    Exceptions.printStackTrace(ex);
+                }
+            }
+        }
+        reporter.finish();
+    }
+
+    public Runnable bench(final Partitioning algorithm, final Graph g, final int maxPartitionSize, final Props props) {
+
+        final Runnable runnable = new Runnable() {
+
+            @Override
+            public void run() {
+                algorithm.partition(maxPartitionSize, g, props);
+            }
+
+        };
+        return runnable;
+    }
+
+    /**
+     * Generate random dataset of doubles with given dimensions
+     *
+     * @param size
+     * @param dim
+     * @return
+     */
+    protected Dataset<? extends Instance> generateData(int size, int dim) {
+        System.out.println("generating data: " + size + " x " + dim);
+        Dataset<? extends Instance> dataset = new ArrayDataset<>(size, dim);
+        for (int i = 0; i < dim; i++) {
+            dataset.attributeBuilder().create("attr-" + i, "NUMERIC");
+        }
+        for (int i = 0; i < size; i++) {
+            dataset.instance(i).setName(String.valueOf(i));
+            for (int j = 0; j < dim; j++) {
+                dataset.set(i, j, rand.nextDouble());
+            }
+        }
+
+        return dataset;
+    }
+
+    private int determineK(Dataset<? extends Instance> dataset) {
+
+        if (dataset.size() < 500) {
+            return (int) (Math.log(dataset.size()) / Math.log(2));
+        } else {
+            return (int) (Math.log(dataset.size()) / Math.log(2)) * 2;
+        }
+    }
+
+    private int determineMaxPartitionSize(Dataset<? extends Instance> dataset) {
+        if (dataset.size() < 500) {
+            return 5;
+        } else if ((dataset.size() < 2000)) {
+            return dataset.size() / 100;
+        } else {
+            return dataset.size() / 200;
+        }
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/partition/PartitionExp.java

@@ -0,0 +1,65 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.partition;
+
+import com.beust.jcommander.JCommander;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import org.clueminer.clustering.benchmark.Bench;
+import static org.clueminer.clustering.benchmark.Bench.ensureFolder;
+import static org.clueminer.clustering.benchmark.Bench.printUsage;
+import org.clueminer.partitioning.api.Partitioning;
+import org.clueminer.partitioning.impl.RecursiveBisection;
+
+/**
+ * An experiment to test time complexity of graph partitioning methods
+ *
+ * @author deric
+ */
+public class PartitionExp extends Bench {
+
+    public static final String name = "partition";
+
+    protected static PartitionParams parseArguments(String[] args) {
+        PartitionParams params = new PartitionParams();
+        JCommander cmd = new JCommander(params);
+        printUsage(args, cmd, params);
+        return params;
+    }
+
+    @Override
+    public void main(String[] args) {
+        PartitionParams params = parseArguments(args);
+
+        benchmarkFolder = params.home + '/' + "benchmark" + '/' + name;
+        ensureFolder(benchmarkFolder);
+        System.out.println("writing results to: " + benchmarkFolder);
+
+        System.out.println("=== starting " + name);
+
+        Partitioning[] algorithms = new Partitioning[]{
+            new RecursiveBisection()
+        };
+
+        Runnable exp = new PartitionBench(params, name, algorithms);
+
+        ExecutorService execService = Executors.newFixedThreadPool(1);
+        execService.submit(exp);
+        execService.shutdown();
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/partition/PartitionParams.java

@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.clustering.benchmark.partition;
+
+import com.beust.jcommander.Parameter;
+import org.clueminer.clustering.benchmark.AbsParams;
+
+/**
+ *
+ * @author deric
+ */
+public class PartitionParams extends AbsParams {
+
+    @Parameter(names = "--n", description = "size of biggest dataset", required = false)
+    public int n = 20;
+
+    @Parameter(names = "--n-small", description = "size of smallest", required = false)
+    public int nSmall = 5;
+
+    @Parameter(names = "--steps", description = "number of datasets which will be generated")
+    public int steps = 4;
+
+    @Parameter(names = "--dimension", description = "number of attributes of each dataset")
+    public int dimension = 5;
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/data/DataLoader.java

@@ -0,0 +1,242 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.data;
+
+import java.io.File;
+import java.io.FileNotFoundException;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.OutputStream;
+import java.net.URL;
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.Map;
+import java.util.TreeMap;
+import org.clueminer.dataset.api.DataProvider;
+import org.clueminer.dataset.api.Dataset;
+import org.clueminer.dataset.api.Instance;
+import org.clueminer.dataset.impl.ArrayDataset;
+import org.clueminer.exception.ParserError;
+import org.clueminer.io.arff.ARFFHandler;
+import org.openide.util.Exceptions;
+
+/**
+ *
+ * @author deric
+ */
+public class DataLoader implements DataProvider {
+
+    private final Map<String, String> datasets;
+    private final Map<String, String> fullPaths;
+    private final Map<String, Dataset<? extends Instance>> cache;
+    private String prefix = "datasets" + File.separatorChar + "artificial";
+
+    public DataLoader(Map<String, String> datasets, String prefix, Map<String, String> fullPaths) {
+        this.datasets = datasets;
+        this.cache = new HashMap<>(datasets.size());
+        this.prefix = prefix;
+        this.fullPaths = fullPaths;
+    }
+
+    @Override
+    public String[] getDatasetNames() {
+        return datasets.keySet().toArray(new String[0]);
+    }
+
+    @Override
+    public Dataset<? extends Instance> getDataset(String name) {
+        if (cache.containsKey(name)) {
+            return cache.get(name);
+        }
+        if (!datasets.containsKey(name)) {
+            throw new RuntimeException("unknown dataset " + name);
+        }
+
+        Dataset<? extends Instance> dataset = loadDataset(name, datasets.get(name), fullPaths.get(name));
+        cache.put(name, dataset);
+        return dataset;
+    }
+
+    @Override
+    public Dataset<? extends Instance> first() {
+        Iterator<String> it = datasets.keySet().iterator();
+        if (!it.hasNext()) {
+            throw new RuntimeException("no datasets were loaded");
+        }
+        return getDataset(it.next());
+    }
+
+    @Override
+    public int count() {
+        return datasets.size();
+    }
+
+    /**
+     * Tries to load dataset by its name. There must be a method for loading the
+     * dataset in this class.
+     *
+     * @param name
+     * @return
+     */
+    private Dataset<? extends Instance> loadDataset(String name, String type, String fullPath) {
+        Dataset<? extends Instance> dataset = null;
+        switch (type) {
+            case "arff":
+                //TODO: multi dimensions support
+                dataset = new ArrayDataset(10, 2);
+                dataset.setName(name);
+                ARFFHandler arff = new ARFFHandler();
+                try {
+                    arff.load(resource(name + "." + type, fullPath), dataset);
+                } catch (FileNotFoundException | ParserError ex) {
+                    Exceptions.printStackTrace(ex);
+                }
+                break;
+            default:
+                throw new RuntimeException("unsupported format " + type);
+        }
+
+        return dataset;
+    }
+
+    /**
+     * Resource packed in jar is not possible to open directly, this method uses
+     * a .tmp file which should be on exit deleted
+     *
+     * @param path
+     * @param fullPath
+     * @return
+     */
+    public File resource(String path, String fullPath) {
+        String resource = prefix + File.separatorChar + path;
+        File file;
+        URL url = DataLoader.class.getResource(resource);
+        if (url == null) {
+            //probably on Windows
+            file = new File(fullPath);
+            if (file.exists()) {
+                return file;
+            }
+            //non existing URL
+            //no classpath, compiled as JAR
+            //if path is in form: "jar:path.jar!resource/data.arff"
+            int pos = fullPath.lastIndexOf("!");
+            if (pos > 0) {
+                resource = fullPath.substring(pos + 1);
+                if (!resource.startsWith("/")) {
+                    //necessary for loading as a stream
+                    resource = "/" + resource;
+                }
+            }
+            return loadResource(resource);
+        }
+
+        if (url.toString().startsWith("jar:")) {
+            return loadResource(resource);
+        } else {
+            file = new File(url.getFile());
+        }
+        return file;
+    }
+
+    private File loadResource(String resource) {
+        File file = null;
+        try {
+            InputStream input = getClass().getResourceAsStream(resource);
+            file = File.createTempFile("nodesfile", ".tmp");
+            OutputStream out = new FileOutputStream(file);
+            int read;
+            byte[] bytes = new byte[1024];
+
+            while ((read = input.read(bytes)) != -1) {
+                out.write(bytes, 0, read);
+            }
+            file.deleteOnExit();
+        } catch (IOException ex) {
+            System.err.println(ex.toString());
+        }
+        return file;
+    }
+
+    public static DataProvider createLoader(String p1, String p2) {
+        String path = p1 + File.pathSeparatorChar + p2;
+        Map<String, String> datasets = new TreeMap<>();
+        Map<String, String> paths = new HashMap<>();
+
+        final Collection<String> list = ResourceList.getResources(p1, p2);
+        int idx, dot;
+        String dataset;
+        String ext;
+        for (final String name : list) {
+            idx = name.lastIndexOf(File.separatorChar);
+            dot = name.lastIndexOf(".");
+            if (dot > 0) {
+                dataset = name.substring(idx + 1, dot);
+            } else {
+                dataset = name;
+            }
+            ext = name.substring(dot + 1);
+            datasets.put(dataset, ext);
+            paths.put(dataset, name);
+        }
+
+        return new DataLoader(datasets, path, paths);
+    }
+
+    @Override
+    public Iterator<Dataset<? extends Instance>> iterator() {
+        return new DataLoaderIterator();
+    }
+
+    @Override
+    public boolean hasDataset(String name) {
+        for (String dataset : datasets.keySet()) {
+            if (name.equals(dataset)) {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    private class DataLoaderIterator implements Iterator<Dataset<? extends Instance>> {
+
+        private final Iterator<String> it;
+
+        public DataLoaderIterator() {
+            it = datasets.keySet().iterator();
+        }
+
+        @Override
+        public boolean hasNext() {
+            return it.hasNext();
+        }
+
+        @Override
+        public Dataset<? extends Instance> next() {
+            return getDataset(it.next());
+        }
+
+        @Override
+        public void remove() {
+            throw new UnsupportedOperationException("not supported yet.");
+        }
+
+    }
+
+}

clustering-benchmark-master/src/main/java/org/clueminer/data/ResourceList.java

@@ -0,0 +1,227 @@
+/*
+ * Copyright (C) 2011-2016 clueminer.org
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.clueminer.data;
+
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.FileNotFoundException;
+import java.io.IOException;
+import java.net.URISyntaxException;
+import java.net.URL;
+import java.net.URLDecoder;
+import java.util.Collection;
+import java.util.Enumeration;
+import java.util.LinkedList;
+import java.util.List;
+import java.util.jar.JarEntry;
+import java.util.jar.JarFile;
+import java.util.regex.Pattern;
+import java.util.zip.ZipEntry;
+import java.util.zip.ZipInputStream;
+import org.openide.util.Exceptions;
+import org.openide.util.Utilities;
+
+/**
+ * code from
+ * @link http://stackoverflow.com/questions/3923129/get-a-list-of-resources-from-classpath-directory
+ * @author deric
+ */
+public class ResourceList {
+
+    private static final String OS = System.getProperty("os.name").toLowerCase();
+
+    /**
+     * for all elements of java.class.path get a Collection of resources Pattern
+     * pattern = Pattern.compile(".*"); gets all resources
+     *
+     * @param p1 first part of path
+     * @param p2 second part of path
+     * @return the resources in the order they are found
+     */
+    public static Collection<String> getResources(String p1, String p2) {
+        final List<String> retval = new LinkedList<>();
+        final String classPath = System.getProperty("java.class.path", ".");
+        String pathSeparator;
+        //platform independent regexp
+        Pattern pattern = Pattern.compile("(.*)" + p1 + "(.)" + p2 + "(.*)");
+        if (isWindows()) {
+            try {
+                Enumeration<URL> en = ResourceList.class.getClassLoader().getResources("datasets");
+                if (en.hasMoreElements()) {
+                    URL metaInf = en.nextElement();
+                    File fileMetaInf = Utilities.toFile(metaInf.toURI());
+                    browseFiles(retval, fileMetaInf, pattern);
+                }
+            } catch (IOException | URISyntaxException ex) {
+                Exceptions.printStackTrace(ex);
+            }
+            if (retval.size() > 0) {
+                return retval;
+            }
+            pathSeparator = ";";
+        } else {
+            pathSeparator = ":";
+        }
+        //when running from IDE we can use classpath a directly read files from disk
+        final String[] classPathElements = classPath.split(pathSeparator);
+        for (final String element : classPathElements) {
+            retval.addAll(getResources(element, pattern));
+        }
+        if (retval.isEmpty()) {
+            //last resort, when compiled into JAR
+            loadFromJar(retval, pattern);
+        }
+        return retval;
+    }
+
+    private static void browseFiles(final List<String> retval, File fileMetaInf, final Pattern pattern) {
+        File[] files = fileMetaInf.listFiles();
+        for (File f : files) {
+            if (f.isDirectory()) {
+                browseFiles(retval, f, pattern);
+            } else {
+                String fileName = f.getAbsolutePath();
+                final boolean accept = pattern.matcher(fileName).matches();
+                if (accept) {
+                    retval.add(fileName);
+                }
+            }
+        }
+    }
+
+    private static Collection<String> getResources(final String element, final Pattern pattern) {
+        final List<String> retval = new LinkedList<>();
+        final File file = new File(element);
+        if (file.isDirectory()) {
+            retval.addAll(getResourcesFromDirectory(file, pattern));
+        } else if (file.exists()) {
+            retval.addAll(getResourcesFromJarFile(file, pattern));
+        } else {
+            System.err.println("can't open file: " + file);
+        }
+        return retval;
+    }
+
+    private static Collection<String> getResourcesFromJarFile(final File file, final Pattern pattern) {
+        final List<String> retval = new LinkedList<>();
+        ZipInputStream zip = null;
+        try {
+            zip = new ZipInputStream(new FileInputStream(file));
+        } catch (FileNotFoundException ex) {
+            Exceptions.printStackTrace(ex);
+        }
+
+        if (zip != null) {
+            try {
+                while (zip.available() == 1) {
+                    final ZipEntry ze = zip.getNextEntry();
+                    final String fileName = ze.getName();
+                    final boolean accept = pattern.matcher(fileName).matches();
+                    if (accept) {
+                        retval.add(fileName);
+                    }
+                    zip.closeEntry();
+                }
+                zip.close();
+            } catch (IOException ex) {
+                Exceptions.printStackTrace(ex);
+            }
+        }
+
+        return retval;
+    }
+
+    private static Collection<String> getResourcesFromDirectory(
+            final File directory,
+            final Pattern pattern) {
+        final List<String> retval = new LinkedList<>();
+        final File[] fileList = directory.listFiles();
+        for (final File file : fileList) {
+            if (file.isDirectory()) {
+                retval.addAll(getResourcesFromDirectory(file, pattern));
+            } else {
+                try {
+                    final String fileName = file.getCanonicalPath();
+                    final boolean accept = pattern.matcher(fileName).matches();
+                    if (accept) {
+                        retval.add(fileName);
+                    }
+                } catch (final IOException e) {
+                    throw new Error(e);
+                }
+            }
+        }
+        return retval;
+    }
+
+    public static boolean isWindows() {
+        return (OS.contains("win"));
+    }
+
+    public static boolean isMac() {
+        return (OS.contains("mac"));
+    }
+
+    public static boolean isUnix() {
+        return (OS.contains("nix") || OS.contains("nux") || OS.contains("aix"));
+    }
+
+    public static boolean isSolaris() {
+        return (OS.contains("sunos"));
+    }
+
+    /**
+     * List resources from compiled JAR and choose those matching some pattern
+     *
+     * @param retval
+     * @param pattern
+     */
+    private static void loadFromJar(List<String> retval, Pattern pattern) {
+        try {
+            Enumeration<URL> en = ResourceList.class.getClassLoader().getResources("datasets");
+            if (en.hasMoreElements()) {
+                URL metaInf = en.nextElement();
+                File file;
+
+                String path = metaInf.getPath();
+                String jarFilePath = path.substring(path.indexOf(":") + 1, path.indexOf("!"));
+                jarFilePath = URLDecoder.decode(jarFilePath, "UTF-8");
+                file = new File(jarFilePath);
+
+                try (JarFile jar = new JarFile(file)) {
+                    JarEntry entry;
+                    String fileName;
+                    Enumeration<JarEntry> enumer = jar.entries();
+                    while (enumer.hasMoreElements()) {
+                        entry = enumer.nextElement();
+                        fileName = entry.getName();
+                        if (pattern.matcher(fileName).matches()) {
+                            //don't add directories
+                            if (!fileName.endsWith("/")) {
+                                retval.add("jar:" + jarFilePath + "!" + fileName);
+                            }
+                        }
+                    }
+
+                }
+            }
+        } catch (IOException ex) {
+            Exceptions.printStackTrace(ex);
+        }
+    }
+
+}

clustering-benchmark-master/src/main/nbm/manifest.mf

@@ -0,0 +1,2 @@
+Manifest-Version: 1.0
+OpenIDE-Module-Localizing-Bundle: org/clueminer/clustering/benchmark/Bundle.properties

clustering-benchmark-master/src/main/resources/datasets/artificial/2d-3c-no123.arff

@@ -0,0 +1,725 @@
+% Data from J. Handl
+% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html
+%
+@RELATION 2d-3c-no123
+
+@ATTRIBUTE a0 REAL
+@ATTRIBUTE a1 REAL
+@ATTRIBUTE class {0,1,2}
+
+@DATA
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@@ -0,0 +1,873 @@
+% Data from J. Handl
+% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html
+%
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@@ -0,0 +1,886 @@
+% Data from J. Handl
+% http://personalpages.manchester.ac.uk/mbs/Julia.Handl/generators.html
+%
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clustering-benchmark-master/src/main/resources/datasets/artificial/3-spiral.arff

@@ -0,0 +1,324 @@
+% Spiral, N=312, M=3, D=2
+% Chang, H. and D.Y. Yeung, Robust path-based spectral clustering. Pattern Recognition, 2008. 41(1): p. 191-203.
+%
+% source: http://cs.joensuu.fi/sipu/datasets/
+%
+@relation 3-spiral
+
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE class {1,2,3}
+
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clustering-benchmark-master/src/main/resources/datasets/artificial/3MC.arff

@@ -0,0 +1,412 @@
+% Dataset from: http://mail.tku.edu.tw/chchou/others/others.htm
+%
+% M. C. Su, C. H. Chou, and C. C. Hsieh, “Fuzzy C-Means Algorithm with a Point Symmetry Distance,” 
+% International Journal of Fuzzy Systems, vol. 7, no. 4, pp. 175-181, 2005.
+%
+@RELATION 3MC
+
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE class {1,2,3}
+
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clustering-benchmark-master/src/main/resources/datasets/artificial/DS-577.arff

@@ -0,0 +1,589 @@
+% Dataset from: http://mail.tku.edu.tw/chchou/others/others.htm
+%
+% M. C. Su, C. H. Chou, and C. C. Hsieh, “Fuzzy C-Means Algorithm with a Point Symmetry Distance,”
+% International Journal of Fuzzy Systems, vol. 7, no. 4, pp. 175-181, 2005.
+%
+@RELATION DS-577
+
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE class {1,2,3}
+
+@DATA
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clustering-benchmark-master/src/main/resources/datasets/artificial/DS-850.arff

@@ -0,0 +1,862 @@
+% Dataset from: http://mail.tku.edu.tw/chchou/others/others.htm
+%
+% M. C. Su, C. H. Chou, and C. C. Hsieh, “Fuzzy C-Means Algorithm with a Point Symmetry Distance,”
+% International Journal of Fuzzy Systems, vol. 7, no. 4, pp. 175-181, 2005.
+%
+@RELATION DS-850
+%
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE CLASS {0,1,2,3,4}
+%
+@DATA
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clustering-benchmark-master/src/main/resources/datasets/artificial/R15.arff

@@ -0,0 +1,610 @@
+% R15, N=600, M=15, D=2
+% Veenman, C.J., M.J.T. Reinders, and E. Backer, A maximum variance cluster algorithm. IEEE Trans. Pattern Analysis and Machine Intelligence, 2002. 24(9): p. 1273-1280.
+%
+@RELATION R15
+
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE class {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}
+
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clustering-benchmark-master/src/main/resources/datasets/artificial/aggregation.arff

@@ -0,0 +1,800 @@
+% Aggregation
+% N=788, M=7, D=2
+% Gionis, A., H. Mannila, and P. Tsaparas, Clustering aggregation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2007. 1(1): p. 1-30.
+% source: http://cs.joensuu.fi/sipu/datasets/
+%
+@relation aggregation
+
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE class {1,2,3,4,5,6,7}
+
+@DATA
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clustering-benchmark-master/src/main/resources/datasets/artificial/aml28.arff

@@ -0,0 +1,819 @@
+% The variant allele frequencies of somatic single nucleotide variants
+% from whole genome sequencing of a AML patient at two time points
+%
+% Miller, C. A., White, B. S., Dees, N. D., Griffith, M., Welch, J. S., Griffith, O. L.,
+% Vij, R., Tomasson, M. H., Graubert, T. A., Walter, M. J., et al. (2014).
+% SciClone: Inferring clonal architecture and tracking the spatial and temporal patterns
+% of tumor evolution. PLoS Comput. Biol., 10(8).
+% 
+@relation aml28
+
+@ATTRIBUTE tumor REAL
+@ATTRIBUTE relapse REAL
+@ATTRIBUTE class {1,2,3,4,5}
+
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clustering-benchmark-master/src/main/resources/datasets/artificial/atom.arff

@@ -0,0 +1,820 @@
+% This Fundamental Clustering Problems Suite (FCPS) may serve as a minimal test for new invented cluster algorithms.
+%
+% Every new invented algorithm should at least cluster the FCPS correctly.
+%
+% The data sets may be used as long as the following citation is referenced in any publication
+% concering any of this data:
+%
+% Alfred Ultsch, Clustering with SOM: U*C, in Proc. Workshop on Self Organizing Feature Maps ,pp 31-37 Paris 2005.
+%
+% main problem: different variances and linear not separable
+%
+@relation atom
+
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE z REAL
+@ATTRIBUTE class {1,2}
+
+@data
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clustering-benchmark-master/src/main/resources/datasets/artificial/blobs.arff

@@ -0,0 +1,311 @@
+% Data generated using Python package 'sklearn' (sklearn.datasets.samples_generator)
+%
+% make_blobs(n_samples=300, centers=centers, cluster_std=0.5, random_state=0)
+%
+@relation blobs
+
+@ATTRIBUTE x REAL
+@ATTRIBUTE y REAL
+@ATTRIBUTE class {0,1,2}
+
+@data
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clustering-benchmark-master/src/main/resources/datasets/artificial/compound.arff

@@ -0,0 +1,410 @@
+% Compound
+% N=399, M=6, D=2
+% Zahn, C.T., Graph-theoretical methods for detecting and describing gestalt clusters. IEEE Transactions on Computers, 1971. 100(1): p. 68-86.
+% source: http://cs.joensuu.fi/sipu/datasets/
+@relation compound
+
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+@ATTRIBUTE y REAL
+@ATTRIBUTE class {1,2,3,4,5,6}
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