tp: add clustering
Vo Van Nghia
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.gitignore
vendored
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@ -618,3 +618,9 @@ $RECYCLE.BIN/
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# Windows shortcuts
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*.lnk
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# Dataset
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tp/clustering/mars/*.csv
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tp/clustering/mars/*.zip
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tp/clustering/ensemble/images/
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tp/clustering/ensemble/representations/
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tp/clustering/agglomerative.ipynb
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tp/clustering/ensemble/data.txt
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To download the FEI dataset and the corresponding extracted CNN feature representations, used in the Ensemble clustering hands-on, please use the following link:
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The representations are .h5 files (read using h5py)
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Each .h5 representation file contains:
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- a "data" key (containing the features)
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- a "labels" key (containing the corresponding ground truth)
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1159
tp/clustering/ensemble/ensemble.ipynb
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tp/clustering/ensemble/stater.ipynb
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BIN
tp/clustering/ensemble/subject.pdf
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tp/clustering/gmm.ipynb
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tp/clustering/images/aggloClustering_linkage_comparison.png
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After Width: | Height: | 크기: 420 KiB |
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tp/clustering/images/clustering_recommender.png
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After Width: | Height: | 크기: 139 KiB |
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tp/clustering/images/example_lego_in.png
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After Width: | Height: | 크기: 155 KiB |
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tp/clustering/images/example_lego_out.png
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After Width: | Height: | 크기: 1.2 MiB |
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tp/clustering/images/example_tools_in.png
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After Width: | Height: | 크기: 588 KiB |
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tp/clustering/images/example_tools_out.jpg
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After Width: | Height: | 크기: 1.9 MiB |
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tp/clustering/images/forest_segmentation.png
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After Width: | Height: | 크기: 248 KiB |
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tp/clustering/images/tumor.jpg
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After Width: | Height: | 크기: 50 KiB |