場(chǎng)景：從樣本集中采樣80%用于訓(xùn)練，20%用于驗(yàn)證。

參考代碼如下：

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));//訓(xùn)練集

System.out.println(datass.y().instance(0));//測(cè)試集

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);

}*/

}

}

總結(jié)

以上是生活随笔為你收集整理的java sampling_Java机器学习库ML之三Sampling(采样)的全部?jī)?nèi)容，希望文章能夠幫你解決所遇到的問(wèn)題。

如果覺(jué)得生活随笔網(wǎng)站內(nèi)容還不錯(cuò)，歡迎將生活随笔推薦給好友。