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 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 pms = EvaluateDataset.testDataset(c, datass.y());

System.out.println(pms);

/*

for (int i = 0; i < 5; i++) {

Pair datas = s.sample(data, (int) (data.size() * 0.8), i);

Classifier c = new LibSVM();

c.buildClassifier(datas.x());

Map pms = EvaluateDataset.testDataset(c, datas.y());

System.out.println(pms);

}*/

}

}