Java机器学习库ML之三Sampling(采样)

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场景：从样本集中采样80%用于训练，20%用于验证。

参考代码如下：

package com.gddx;import java.io.File;import java.util.Map;import libsvm.LibSVM;import net.sf.javaml.classification.Classifier;import net.sf.javaml.classification.evaluation.EvaluateDataset;import net.sf.javaml.classification.evaluation.PerformanceMeasure;import net.sf.javaml.core.Dataset;import net.sf.javaml.sampling.Sampling;import net.sf.javaml.tools.data.FileHandler;import be.abeel.util.Pair;/** * Sample program illustrating how to use sampling. *  * @author Thomas Abeel *  */public class TutorialSampling {public static void main(String[] args) throws Exception {Dataset data = FileHandler.loadDataset(new File("D:\\tmp\\javaml-0.1.7-src\\UCI-small\\iris\\iris.data"), 4, ",");Sampling s = Sampling.SubSampling;Pair<Dataset, Dataset> datass = s.sample(data, (int) (data.size() * 0.8));System.out.println(datass.x().instance(0));//训练集System.out.println(datass.y().instance(0));//测试集Classifier c = new LibSVM();c.buildClassifier(datass.x());Map<Object,PerformanceMeasure> pms = EvaluateDataset.testDataset(c, datass.y());System.out.println(pms);        /*for (int i = 0; i < 5; i++) {Pair<Dataset, Dataset> datas = s.sample(data, (int) (data.size() * 0.8), i);Classifier c = new LibSVM();c.buildClassifier(datas.x());Map<Object,PerformanceMeasure> pms = EvaluateDataset.testDataset(c, datas.y());System.out.println(pms);}*/}}

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