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学习过程中理解算法参考了#xff1a;#xff08;十三#xff09;通俗易懂理解——Adaboost算法原… 代码来自闵老师”日撸 Java 三百行61-70天
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学习过程中理解算法参考了十三通俗易懂理解——Adaboost算法原理 - 知乎 (zhihu.com) 今天的代码的核心是方法adjustWeights(boolean[] paraCorrectArray, double paraAlpha)。分类正确的实例权重调整为原值除以Math.exp(paraAlpha)分类错误的调整为原值乘以Math.exp(paraAlpha)。
测试方法里之所以for循环到tempCorrectArray长度的一半仅仅是为了测试。相当于设置弱分类器分类正确了一半。
package machinelearning.adaboosting;import java.io.FileReader;
import java.util.Arrays;import weka.core.Instances;/*** Weighted instances.br* * author WX873**/
public class WeightedInstances extends Instances{/*** Just the requirement of some classes, any number is ok.*/private static final long serialVersionUID 11087456L;/*** Weights*/private double[] weights;/*** *************************************************** The first constructor.* * param paraFileReader The given reader to read data from file.* throws Exception* ***************************************************/public WeightedInstances(FileReader paraFileReader) throws Exception{// TODO Auto-generated constructor stubsuper(paraFileReader);setClassIndex(numAttributes() - 1);// Initialize weightsweights new double[numInstances()];double tempAverage 1.0/numInstances();for (int i 0; i weights.length; i) {weights[i] tempAverage;}//of for iSystem.out.println(Instances weights are: Arrays.toString(weights));}//of the first constructor/*** *********************************************************** The second constructor.* * param paraInstances* ***********************************************************/public WeightedInstances(Instances paraInstances) {// TODO Auto-generated constructor stubsuper(paraInstances);setClassIndex(numAttributes() - 1);//Initialize weightsweights new double[numInstances()];double tempAverage 1.0/numInstances();for (int i 0; i weights.length; i) {weights[i] tempAverage;}//of for iSystem.out.println(Instances weights are: Arrays.toString(weights));}//of the second constructor/*** **************************************************** Getter.* * param paraIndex The given index.* return The weight of the given index.* ****************************************************/public double getWeight(int paraIndex) {return weights[paraIndex];}//of getWeight/*** ****************************************************** Adjust the weights.* * param paraCorrectArray Indicate which instances have been correctly classified.* param paraAlpha The weight of the last classifier.* ******************************************************/public void adjustWeights(boolean[] paraCorrectArray, double paraAlpha) {//Step 1. Calculate alpha.double tempIncrease Math.exp(paraAlpha);//Step 2. Adjust.double tempWeightsSum 0; // For normalization.for (int i 0; i weights.length; i) {if (paraCorrectArray[i]) {weights[i] / tempIncrease;} else {weights[i] * tempIncrease;}//of iftempWeightsSum weights[i];}//of for i// Step 3. Normalize.for (int i 0; i weights.length; i) {weights[i] / tempWeightsSum;}//of for iSystem.out.println(After adjusting, instances weights are: Arrays.toString(weights));}//of adjustWeights/*** ********************************************** Test the method.* **********************************************/public void adjustWeightsTest() {boolean[] tempCorrectArray new boolean[numInstances()];for (int i 0; i tempCorrectArray.length / 2; i) { //仅仅是测试adjustWeights方法,因为还没有分类器设置分类正确了一半tempCorrectArray[i] true;}//of for idouble tempWeightedError 0.3;adjustWeights(tempCorrectArray, tempWeightedError); //仅仅是测试adjustWeights方法,因为还没有分类器System.out.println(After adjusting);System.out.println(toString());}//of adjustWeightsTest/*** ********************************************************* For display.* *********************************************************/public String toString() {String resultString I am a weighted Instances object.\r\n I have numInstances() instances and (numAttributes() - 1) conditional attributes.\r\n My weights are: Arrays.toString(weights) \r\n My data are: \r\n super.toString();return resultString;}//of toString/*** ************************************************************ The entrance of the program.* * param args* ************************************************************/public static void main(String args[]) {WeightedInstances tempWeightedInstances null;String tempFilename E:/Datasets/UCIdatasets/其他数据集/iris.arff;try {FileReader tempFileReader new FileReader(tempFilename);tempWeightedInstances new WeightedInstances(tempFileReader);tempFileReader.close();} catch (Exception exception1) {// TODO: handle exceptionSystem.out.println(Cannot read the file: tempFilename \r\n exception1);System.exit(0);}//of trySystem.out.println(tempWeightedInstances.toString());tempWeightedInstances.adjustWeightsTest();}//of main}//of WeightedInstances
