多维k-means聚类算法java实现，导入直接运行

多维k-means聚类算法java简单实现，导入运行KmeansTest.java可看到结果

package com.kmeans;

import java.util.Arrays;
import java.util.Collections;
import java.util.linkedList;
import java.util.List;
import java.util.Random;

/**
 * 
 * @author Yuanbo She
 * 
 */
public class Kmeans {

    /**
     * double[][] 元素全置0
     * 
     * @param matrix
     *            double[][]
     * @param highDim
     *            int
     * @param lowDim
     *            int 

     *            double[highDim][lowDim]
     */
    private static void setDouble2Zero（double[][] matrix int highDim int lowDim） {
        for （int i = 0; i < highDim; i++） {
            for （int j = 0; j < lowDim; j++） {
                matrix[i][j] = 0;
            }
        }
    }

    /**
     * 拷贝源二维矩阵元素到目标二维矩阵。 foreach （dests[highDim][lowDim] = sources[highDim][lowDim]）;
     * 
     * @param dests
     *            double[][]
     * @param sources
     *            double[][]
     * @param highDim
     *            int
     * @param lowDim
     *            int
     */
    private static void copyCenters（double[][] dests double[][] sources int highDim int lowDim） {
        for （int i = 0; i < highDim; i++） {
            for （int j = 0; j < lowDim; j++） {
                dests[i][j] = sources[i][j];
            }
        }
    }

    /**
     * 更新聚类中心坐标
     * 
     * @param k
     *            int 分类个数
     * @param data
     *            kmeans_data
     */
    private static void updateCenters（int k Kmeans_data data） {
        double[][] centers = data.centers;
        setDouble2Zero（centers k data.dim）;
        int[] labels = data.labels;
        int[] centerCounts = data.centerCounts;
        for （int i = 0; i < data.dim; i++） {
            for （int j = 0; j < data.length; j++） {
                centers[labels[j]][i] += data.data[j][i];
            }
        }
        for （int i = 0; i < k; i++） {
            for （int j = 0; j < data.dim; j++） {
                centers[i][j] = centers[i][j] / centerCounts[i];
            }
        }
    }

    /**
     * 计算两点欧氏距离
     * 
     * @param pa
     *            double[]
     * @param pb
     *            double[]
     * @param dim
     *            int 维数
     * @return double 距离
     */
    public static double dist（double[] pa double[] pb int dim） {
        double rv = 0;
        for （int i = 0; i < dim; i++） {
            double temp = pa[i] - pb[i];
            temp = temp * temp;
            rv += temp;
        }
        return Math.sqrt（rv）;
    }

    /**
     * 做Kmeans运算
     * 
     * @param k
     *            int 聚类个数
     * @param data
     *            kmeans_data kmeans数据类
     * @param param
     *            kmeans_param kmeans参数类
     * @return kmeans_result kmeans运行信息类
     */
    public static Kmeans_result doKmeans（int k Kmeans_data data Kmeans_param param） {
        // 预处理
        double[][] centers = new double[k][data.dim]; // 聚类中心点集
        data.cente

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     文件         301  2014-05-06 16:56  kmeans\.classpath
     文件         382  2014-05-06 16:56  kmeans\.project
     文件          78  2014-05-06 16:56  kmeans\.settings\org.eclipse.core.resources.prefs
     文件         598  2014-05-06 16:56  kmeans\.settings\org.eclipse.jdt.core.prefs
     文件        5167  2014-05-06 17:01  kmeans\bin\com\kmeans\Kmeans.class
     文件        1483  2014-05-06 17:01  kmeans\bin\com\kmeans\KmeansTest.class
     文件         501  2014-05-06 17:01  kmeans\bin\com\kmeans\Kmeans_data.class
     文件         627  2014-05-06 17:01  kmeans\bin\com\kmeans\Kmeans_param.class
     文件         358  2014-05-06 17:01  kmeans\bin\com\kmeans\Kmeans_result.class
     文件          24  2014-05-06 16:44  kmeans\bin\com\kmeans\readme.txt
     文件        8176  2014-05-06 16:56  kmeans\src\com\kmeans\Kmeans.java
     文件         709  2014-05-06 16:56  kmeans\src\com\kmeans\KmeansTest.java
     文件         879  2014-05-06 16:56  kmeans\src\com\kmeans\Kmeans_data.java
     文件         529  2014-05-06 17:01  kmeans\src\com\kmeans\Kmeans_param.java
     文件         286  2014-05-06 16:56  kmeans\src\com\kmeans\Kmeans_result.java
     文件          24  2014-05-06 16:44  kmeans\src\com\kmeans\readme.txt