k-均值算法的java实现

import java.io.BufferedReader;
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.io.IOException;

public class KAverage {
	private int sampleCount = 0;
	private int dimensionCount = 0;
	private int centerCount = 0;
	private double[][] sampleValues;
	private double[][] centers;
	private double[][] tmpCenters;
	private String dataFile = "";

	/**
	 * 通过构造器传人数据文件
	 */
	public KAverage(String dataFile) throws NumberInvalieException {
		this.dataFile = dataFile;
	}

	/**
	 * 第一行为s;d;c含义分别为样例的数目，每个样例特征的维数，聚类中心个数 文件格式为d[,d]...;d[,d]... 如：1,2;2,3;1,5
	 * 每一维之间用,隔开，每个样例间用;隔开。结尾没有';' 可以有多行
	 */

	private int initData(String fileName) {
		String line;
		String samplesValue[];
		String dimensionsValue[] = new String[dimensionCount];
		BufferedReader in;
		try {
			in = new BufferedReader(new FileReader(fileName));
		} catch (FileNotFoundException e) {
			e.printStackTrace();
			return -1;
		}
		/*
		 * 预处理样本，允许后面几维为0时，不写入文件
		 */
		for (int i = 0; i < sampleCount; i++) {
			for (int j = 0; j < dimensionCount; j++) {
				sampleValues[i][j] = 0;
			}
		}

		int i = 0;
		double tmpValue = 0.0;
		try {
			line = in.readLine();
			String params[] = line.split(";");
			if (params.length != 3) {// 必须为3个参数，否则错误
				return -1;
			}
			/**
			 * 获取参数
			 */
			this.sampleCount = Integer.parseInt(params[0]);
			this.dimensionCount = Integer.parseInt(params[1]);
			this.centerCount = Integer.parseInt(params[2]);
			if (sampleCount <= 0 || dimensionCount <= 0 || centerCount <= 0) {
				throw new NumberInvalieException("input number <= 0.");
			}
			if (sampleCount < centerCount) {
				throw new NumberInvalieException(
						"sample number < center number");
			}

			sampleValues = new double[sampleCount][dimensionCount + 1];
			centers = new double[centerCount][dimensionCount];
			tmpCenters = new double[centerCount][dimensionCount];

			while ((line = in.readLine()) != null) {
				samplesValue = line.split(";");
				for (int j = 0; j < samplesValue.length; j++) {
					dimensionsValue = samplesValue[j].split(",");
					for (int k = 0; k < dimensionsValue.length; k++) {
						tmpValue = Double.parseDouble(dimensionsValue[k]);
						sampleValues[i][k] = tmpValue;
					}
					i++;
				}
			}

		} catch (IOException e) {
			e.printStackTrace();
			return -2;
		} catch (Exception e) {
			e.printStackTrace();
			return -3;
		}
		return 1;
	}

	/**
	 * 返回样本中第s1个和第s2个间的欧式距离
	 */
	private double getDistance(int s1, int s2) throws NumberInvalieException {
		double distance = 0.0;
		if (s1 < 0 || s1 >= sampleCount || s2 < 0 || s2 >= sampleCount) {
			throw new NumberInvalieException("number out of bound.");
		}
		for (int i = 0; i < dimensionCount; i++) {
			distance += (sampleValues[s1][i] - sampleValues[s2][i])
					* (sampleValues[s1][i] - sampleValues[s2][i]);
		}

		return distance;
	}

	/**
	 * 返回给定两个向量间的欧式距离
	 */
	private double getDistance(double s1[], double s2[]) {
		double distance = 0.0;
		for (int i = 0; i < dimensionCount; i++) {
			distance += (s1[i] - s2[i]) * (s1[i] - s2[i]);
		}
		return distance;
	}

	/**
	 * 更新样本中第s个样本的最近中心
	 */
	private int getNearestCenter(int s) {
		int center = 0;
		double minDistance = Double.MAX_VALUE;
		double distance = 0.0;
		for (int i = 0; i < centerCount; i++) {
			distance = getDistance(sampleValues[s], centers[i]);
			if (distance < minDistance) {
				minDistance = distance;
				center = i;
			}
		}
		sampleValues[s][dimensionCount] = center;
		return center;
	}

	/**
	 * 更新所有中心
	 */
	private void updateCenters() {
		double center[] = new double[dimensionCount];
		for (int i = 0; i < dimensionCount; i++) {
			center[i] = 0;
		}
		int count = 0;
		for (int i = 0; i < centerCount; i++) {
			count = 0;
			for (int j = 0; j < sampleCount; j++) {
				if (sampleValues[j][dimensionCount] == i) {
					count++;
					for (int k = 0; k < dimensionCount; k++) {
						center[k] += sampleValues[j][k];
					}
				}
			}
			for (int j = 0; j < dimensionCount; j++) {
				centers[i][j] = center[j] / count;
			}
		}
	}

	/**
	 * 判断算法是否终止
	 */
	private boolean toBeContinued() {
		for (int i = 0; i < centerCount; i++) {
			for (int j = 0; j < dimensionCount; j++) {
				if (tmpCenters[i][j] != centers[i][j]) {
					return true;
				}
			}
		}
		return false;
	}

	/**
	 * 关键方法，调用其他方法，处理数据
	 */
	public void doCaculate() {
		initData(dataFile);

		for (int i = 0; i < centerCount; i++) {
			for (int j = 0; j < dimensionCount; j++) {
				centers[i][j] = sampleValues[i][j];
			}
		}
		for (int i = 0; i < centerCount; i++) {
			for (int j = 0; j < dimensionCount; j++) {
				tmpCenters[i][j] = 0;
			}
		}

		while (toBeContinued()) {
			for (int i = 0; i < sampleCount; i++) {
				getNearestCenter(i);
			}
			for (int i = 0; i < centerCount; i++) {
				for (int j = 0; j < dimensionCount; j++) {
					tmpCenters[i][j] = centers[i][j];
				}
			}
			updateCenters();
			System.out
					.println("******************************************************");
			showResultData();
		}
	}

	/*
	 * 显示数据
	 */
	private void showSampleData() {
		for (int i = 0; i < sampleCount; i++) {
			for (int j = 0; j < dimensionCount; j++) {
				if (j == 0) {
					System.out.print(sampleValues[i][j]);
				} else {
					System.out.print("," + sampleValues[i][j]);
				}
			}
			System.out.println();
		}
	}

	/*
	 * 分组显示结果
	 */
	private void showResultData() {
		for (int i = 0; i < centerCount; i++) {
			System.out.println("第" + (i + 1) + "个分组内容为:");
			for (int j = 0; j < sampleCount; j++) {
				if (sampleValues[j][dimensionCount] == i) {
					for (int k = 0; k <= dimensionCount; k++) {
						if (k == 0) {
							System.out.print(sampleValues[j][k]);
						} else {
							System.out.print("," + sampleValues[j][k]);
						}
					}
					System.out.println();
				}
			}
		}
	}

	public static void main(String[] args) {
		/*
		 *也可以通过命令行得到参数
		 */
		String fileName = "D:\\eclipsejava\\K-Average\\src\\sample.txt";
		if(args.length > 0){
			fileName = args[0];
		}

		try {
			KAverage ka = new KAverage(fileName);
			ka.doCaculate();
			System.out
					.println("***************************<<result>>**************************");
			ka.showResultData();
		} catch (Exception e) {
			e.printStackTrace();
		}
	}
}

/*
 * 根据自己的需要定义一些异常，使得系统性更强
 */
public class NumberInvalieException extends Exception {
	private String cause;

	public NumberInvalieException(String cause){
		if(cause == null || "".equals(cause)){
			this.cause = "unknow";
		}else{
			this.cause = cause;
		}
	}
	@Override
	public String toString() {
		return "Number Invalie!Cause by " + cause;
	}
}

测试数据
20;2;4
0,0;1,0;0,1;1,1;2,1;1,2;2,2;3,2;6,6;7,6
8,6;6,7;7,7;8,7;9,7;7,8;8,8;9,8;8,9;9,9
测试结果
***************************<<result>>**************************
第1个分组内容为:
0.0,0.0,0.0
1.0,0.0,0.0
0.0,1.0,0.0
1.0,1.0,0.0
2.0,1.0,0.0
1.0,2.0,0.0
2.0,2.0,0.0
3.0,2.0,0.0
第2个分组内容为:
6.0,6.0,1.0
7.0,6.0,1.0
8.0,6.0,1.0
6.0,7.0,1.0
7.0,7.0,1.0
8.0,7.0,1.0
9.0,7.0,1.0
7.0,8.0,1.0
8.0,8.0,1.0
9.0,8.0,1.0
8.0,9.0,1.0
9.0,9.0,1.0