lidapeng
5 years ago
parent
d8d6a3197c
commit
f1cf3de0f2
@ -0,0 +1,124 @@
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@ -0,0 +1,131 @@
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package org.wlld.imageRecognition.border;
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import org.wlld.MatrixTools.Matrix;
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import org.wlld.MatrixTools.MatrixOperation;
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import org.wlld.tools.ArithUtil;
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import java.util.*;
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/**
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* @author lidapeng
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* @description //k均值聚类工具
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* @date 10:14 上午 2020/2/4
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*/
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public class KClustering {
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private List<MatrixBody> matrixList = new ArrayList<>();//聚类集合
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private int length;//向量长度
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private int speciesQuantity;//种类数量
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private Matrix[] matrices = new Matrix[speciesQuantity];//均值K
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private Map<Integer, List<MatrixBody>> clusterMap = new HashMap<>();//簇
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public Matrix[] getMatrices() {
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return matrices;
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}
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public Map<Integer, List<MatrixBody>> getClusterMap() {
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return clusterMap;
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}
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public KClustering(int speciesQuantity) {
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this.speciesQuantity = speciesQuantity;
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for (int i = 0; i < speciesQuantity; i++) {
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clusterMap.put(i, new ArrayList<>());
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}
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}
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public void setMatrixList(MatrixBody matrixBody) throws Exception {
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if (matrixBody.getMatrix().isVector() && matrixBody.getMatrix().isRowVector()) {
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Matrix matrix = matrixBody.getMatrix();
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if (matrixList.size() == 0) {
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matrixList.add(matrixBody);
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length = matrix.getY();
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} else {
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if (length == matrix.getY()) {
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matrixList.add(matrixBody);
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} else {
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throw new Exception("vector length is different");
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}
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}
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} else {
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throw new Exception("this matrix is not vector or rowVector");
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}
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}
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private Matrix[] averageMatrix() throws Exception {
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Matrix[] matrices2 = new Matrix[speciesQuantity];//待比较均值K
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for (MatrixBody matrixBody : matrixList) {//遍历当前集合
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Matrix matrix = matrixBody.getMatrix();
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double min = 0;
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int id = 0;
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for (int i = 0; i < matrices.length; i++) {
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double dist = MatrixOperation.getEDist(matrix, matrices[i]);
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if (min == 0 || dist < min) {
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min = dist;
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id = i;
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}
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}
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List<MatrixBody> matrixList1 = clusterMap.get(id);
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matrixList1.add(matrixBody);
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}
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//重新计算均值
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for (Map.Entry<Integer, List<MatrixBody>> entry : clusterMap.entrySet()) {
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Matrix matrix = average(entry.getValue());
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matrices2[entry.getKey()] = matrix;
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}
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return matrices2;
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}
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private void clear() {
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for (Map.Entry<Integer, List<MatrixBody>> entry : clusterMap.entrySet()) {
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entry.getValue().clear();
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}
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}
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private Matrix average(List<MatrixBody> matrixList) throws Exception {//进行矩阵均值计算
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double nub = ArithUtil.div(1, matrixList.size());
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Matrix matrix = new Matrix(0, length);
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for (MatrixBody matrixBody1 : matrixList) {
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matrix = MatrixOperation.add(matrix, matrixBody1.getMatrix());
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}
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MatrixOperation.mathMul(matrix, nub);
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return matrix;
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}
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public void start() throws Exception {//开始聚类
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if (matrixList.size() > 1) {
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Random random = new Random();
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for (int i = 0; i < matrices.length; i++) {//初始化均值向量
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int index = random.nextInt(matrixList.size());
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matrices[i] = matrixList.get(index).getMatrix();
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}
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//进行两者的比较
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boolean isEqual = false;
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do {
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Matrix[] matrices2 = averageMatrix();
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isEqual = equals(matrices, matrices2);
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if (!isEqual) {
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matrices = matrices2;
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clear();
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}
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}
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while (isEqual);
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} else {
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throw new Exception("matrixList number less than 2");
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}
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}
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public boolean equals(Matrix[] matrices1, Matrix[] matrices2) throws Exception {
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boolean isEquals = true;
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for (int i = 0; i < matrices1.length; i++) {
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Matrix matrix1 = matrices1[i];
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Matrix matrix2 = matrices2[i];
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for (int j = 0; j < length; j++) {
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if (matrix1.getNumber(0, j) != matrix2.getNumber(0, j)) {
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isEquals = false;
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break;
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}
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}
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}
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return isEquals;
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}
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}
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@ -0,0 +1,108 @@
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package org.wlld.imageRecognition.border;
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import org.wlld.MatrixTools.Matrix;
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import org.wlld.MatrixTools.MatrixOperation;
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import org.wlld.tools.ArithUtil;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Random;
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/**
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* @author lidapeng
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* @description LVQ 向量量化
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* @date 5:36 下午 2020/2/4
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*/
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public class LVQ {
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private int typeNub;//原型聚类个数,即分类个数
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private MatrixBody[] model = new MatrixBody[typeNub];//原型向量
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private List<MatrixBody> matrixList = new ArrayList<>();
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private double studyPoint = 0.1;//量化学习率
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private int length;//向量长度
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public LVQ(int typeNub) {
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this.typeNub = typeNub;
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}
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public MatrixBody[] getModel() {
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return model;
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}
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public void insertMatrixBody(MatrixBody matrixBody) throws Exception {
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if (matrixBody.getMatrix().isVector() && matrixBody.getMatrix().isRowVector()) {
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Matrix matrix = matrixBody.getMatrix();
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if (matrixList.size() == 0) {
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matrixList.add(matrixBody);
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length = matrix.getY();
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} else {
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if (length == matrix.getY()) {
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matrixList.add(matrixBody);
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} else {
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throw new Exception("vector length is different");
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}
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}
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} else {
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throw new Exception("this matrix is not vector or rowVector");
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}
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}
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private double study() throws Exception {
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double error = 0;
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for (MatrixBody matrixBody : matrixList) {
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Matrix matrix = matrixBody.getMatrix();//特征向量
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long type = matrixBody.getId();//类别
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for (int i = 0; i < typeNub; i++) {
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MatrixBody modelBody = model[i];
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Matrix modelMatrix = modelBody.getMatrix();
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long id = modelBody.getId();
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boolean isRight = id == type;//类别是否相同
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//对矩阵进行修正
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Matrix matrix1 = op(matrix, modelMatrix, isRight);
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//修正矩阵与原矩阵的范数差
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double dist = vectorEqual(modelMatrix, matrix1);
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//将修正后的向量进行赋值
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modelBody.setMatrix(matrix1);
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//统计变化值
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error = ArithUtil.add(error, dist);
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}
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}
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return error;
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}
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//比较两个向量之间的范数差
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private double vectorEqual(Matrix matrix1, Matrix matrix2) throws Exception {
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Matrix matrix = MatrixOperation.sub(matrix1, matrix2);
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return MatrixOperation.getNorm(matrix);
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}
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private Matrix op(Matrix matrix, Matrix modelMatrix, boolean isRight) throws Exception {
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Matrix matrix1 = MatrixOperation.sub(matrix, modelMatrix);
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MatrixOperation.mathMul(matrix1, studyPoint);
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Matrix matrix2;
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if (isRight) {
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matrix2 = MatrixOperation.add(modelMatrix, matrix1);
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} else {
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matrix2 = MatrixOperation.sub(modelMatrix, matrix1);
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}
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return matrix2;
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}
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public void start() throws Exception {//开始向量量化聚类
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Random random = new Random();
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for (int i = 0; i < typeNub; i++) {
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MatrixBody matrixBody = new MatrixBody();
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Matrix matrix = new Matrix(1, length);
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matrixBody.setMatrix(matrix);
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matrixBody.setId(i);
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for (int j = 0; j < length; j++) {
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matrix.setNub(0, j, random.nextInt(10));
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}
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model[i] = matrixBody;
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}
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//初始化完成
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for (int k = 0; k < 1000; k++) {
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double error = study();
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System.out.println("error==" + error);
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}
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}
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}
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@ -0,0 +1,29 @@
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package org.wlld.imageRecognition.border;
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import org.wlld.MatrixTools.Matrix;
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/**
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* @author lidapeng
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* @description
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* @date 3:33 下午 2020/2/4
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*/
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public class MatrixBody {//给矩阵绑定一个id
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private int id;//唯一ID
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private Matrix matrix;//矩阵
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public int getId() {
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return id;
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}
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public void setId(int id) {
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this.id = id;
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}
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public Matrix getMatrix() {
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return matrix;
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}
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public void setMatrix(Matrix matrix) {
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this.matrix = matrix;
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}
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||||
}
|
||||
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Reference in new issue