tp-apprentissage/clustering-benchmark-master/src/main/java/org/clueminer/clustering/benchmark/nsga/NsgaParams.java
Titouan Labourdette e3009c62af 1er commit
2021-09-28 15:35:45 +02:00

55 linhas
2 KiB
Java

/*
* 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;
}