日撸代码300行：第63天(集成学习之 AdaBoosting-1)

 代码来自闵老师”日撸 Java 三百行（61-70天）

日撸 Java 三百行（61-70天，决策树与集成学习）_闵帆的博客-CSDN博客

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