K-means的步骤
输入： 含n 个样本的数据集，簇的数据K
输出： K 个簇
算法步骤：
1.初始化K个簇类中心C1，C2，-……Ck （通常随机选择）
2.repeat 步骤3,4
3，将数据集中的每个样本分配到与之最近的中心Ci所在的簇Cj ；
4. 更新聚类中心Ci,即计算各个簇的样本均值；
5.直到样本分配不在改变
上代码：
import java.lang.annotation.ElementType; import java.lang.annotation.Retention; import java.lang.annotation.RetentionPolicy; import java.lang.annotation.Target; /** * 在对象的属性上标注此注释， * 表示纳入kmeans算法,仅支持数值类属性 * @author 阿飞哥 */ @Retention(RetentionPolicy.RUNTIME) @Target(ElementType.FIELD) public @interface KmeanField { }
import java.lang.annotation.Annotation; import java.lang.reflect.Field; import java.lang.reflect.Method; import java.util.ArrayList; import java.util.List; /** * * @author 阿飞哥 * */ public class Kmeans<T> { /** * 所有数据列表 */ private List<T> players = new ArrayList<T>(); /** * 数据类别 */ private Class<T> classT; /** * 初始化列表 */ private List<T> initPlayers; /** * 需要纳入kmeans算法的属性名称 */ private List<String> fieldNames = new ArrayList<String>(); /** * 分类数 */ private int k = 1; public Kmeans() { } /** * 初始化列表 * * @param list * @param k */ public Kmeans(List<T> list, int k) { this.players = list; this.k = k; T t = list.get(0); this.classT = (Class<T>) t.getClass(); Field[] fields = this.classT.getDeclaredFields(); System.out.println("fields---------------------------------------------="+fields.length); for (int i = 0; i < fields.length; i++) { Annotation kmeansAnnotation = fields[i] .getAnnotation(KmeanField.class); if (kmeansAnnotation != null) { fieldNames.add(fields[i].getName()); System.out.println("fieldNames.add"+ fields[i].getName()); } } initPlayers = new ArrayList<T>(); for (int i = 0; i < k; i++) { initPlayers.add(players.get(i)); } } public List<T>[] comput() { List<T>[] results = new ArrayList[k]; boolean centerchange = true; while (centerchange) { centerchange = false; for (int i = 0; i < k; i++) { results[i] = new ArrayList<T>(); } for (int i = 0; i < players.size(); i++) { T p = players.get(i); double[] dists = new double[k]; for (int j = 0; j < initPlayers.size(); j++) { T initP = initPlayers.get(j); /* 计算距离 */ double dist = distance(initP, p); // double dist = 1.0; // double dist = LevenshteinDistance.levenshteinDistance(initP, p); // System.out.println("dist="+dist); dists[j] = dist; } int dist_index = computOrder(dists); // System.out.println("dist_index="+dist_index); results[dist_index].add(p); } // System.out.println("results[0].size()="+results[0].size()); for (int i = 0; i < k; i++) { // 在每一个簇中寻找中心点 T player_new = findNewCenter(results[i]); // System.out.println( "results[i]"+i+"----"+k+"---===="+results[i].size() +"===="+player_new.toString()); T player_old = initPlayers.get(i); if (!IsPlayerEqual(player_new, player_old)) { centerchange = true; initPlayers.set(i, player_new); } } } // System.out.println( "results+"+results.length); return results; } /** * 比较是否两个对象是否属性一致 * * @param p1 * @param p2 * @return */ public boolean IsPlayerEqual(T p1, T p2) { if (p1 == p2) { return true; } if (p1 == null || p2 == null) { return false; } boolean flag = true; try { for (int i = 0; i < fieldNames.size(); i++) { String fieldName=fieldNames.get(i); String getName = "get" + fieldName.substring(0, 1).toUpperCase() + fieldName.substring(1); // System.out.println(fieldNames); Object value1 = invokeMethod(p1,getName,null); Object value2 = invokeMethod(p2,getName,null); if (!value1.equals(value2)) { flag = false; break; } } } catch (Exception e) { e.printStackTrace(); flag = false; } return flag; } /** * 得到新聚类中心对象 * * @param ps * @return */ public T findNewCenter(List<T> ps) { try { T t = classT.newInstance(); if (ps == null || ps.size() == 0) { return t; } double[] ds = new double[fieldNames.size()]; for (T vo : ps) { for (int i = 0; i < fieldNames.size(); i++) { String fieldName=fieldNames.get(i); String getName = "get" + fieldName.substring(0, 1).toUpperCase() + fieldName.substring(1); Object obj=invokeMethod(vo,getName,null); Double fv=(obj==null?0:Double.parseDouble(obj+"")); ds[i] += fv; } } // System.out.println("-----------------"); for (int i = 0; i < fieldNames.size(); i++) { ds[i] = ds[i] / ps.size(); // 平均距离 String fieldName = fieldNames.get(i); /* 给对象设值 */ String setName = "set" + fieldName.substring(0, 1).toUpperCase() + fieldName.substring(1); // invokeMethod(t,setName,new Class[]{double.class},ds[i]); System.out.println("ds[i] ++="+ds[i]+"----ps.size()"+ps.size()); invokeMethod(t,setName,new Class[]{double.class},ds[i]); } return t; } catch (Exception ex) { ex.printStackTrace(); } return null; } /** * 得到最短距离，并返回最短距离索引 * * @param dists * @return */ public int computOrder(double[] dists) { double min = 0; int index = 0; for (int i = 0; i < dists.length - 1; i++) { double dist0 = dists[i]; if (i == 0) { min = dist0; index = 0; } double dist1 = dists[i + 1]; if (min > dist1) { min = dist1; index = i + 1; } } return index; } /** * 计算距离（相似性） 采用欧几里得算法 * * @param p0 * @param p1 * @return */ public double distance(T p0, T p1) { double dis = 0; try { for (int i = 0; i < fieldNames.size(); i++) { String fieldName = fieldNames.get(i); String getName = "get" + fieldName.substring(0, 1).toUpperCase() + fieldName.substring(1); // System.out.println("fieldNames-----="+fieldNames.size()); Double field0Value=Double.parseDouble(invokeMethod(p0,getName,null)+""); Double field1Value=Double.parseDouble(invokeMethod(p1,getName,null)+""); // System.out.println("field0Value="+field0Value); dis += Math.pow(field0Value - field1Value, 2); } } catch (Exception ex) { ex.printStackTrace(); } return Math.sqrt(dis); } /*------公共方法-----*/ public Object invokeMethod(Object owner, String methodName,Class[] argsClass, Object... args) { Class ownerClass = owner.getClass(); try { Method method=ownerClass.getDeclaredMethod(methodName,argsClass); return method.invoke(owner, args); } catch (SecurityException e) { e.printStackTrace(); } catch (NoSuchMethodException e) { e.printStackTrace(); } catch (Exception ex) { ex.printStackTrace(); } return null; } }
public class Player { private int id; //@KmeanField private String name; private int age; /* 得分 */ @KmeanField private double goal; /* 助攻 */ //@KmeanField private double assists; /* 篮板 */ //@KmeanField private double backboard; /* 抢断 */ //@KmeanField private double steals; public int getId() { return id; } public void setId(int id) { this.id = id; } public String getName() { return name; } public void setName(String name) { this.name = name; } public int getAge() { return age; } public void setAge(int age) { this.age = age; } public double getGoal() { return goal; } public void setGoal(double goal) { this.goal = goal; } public double getAssists() { return assists; } public void setAssists(double assists) { this.assists = assists; } public double getBackboard() { return backboard; } public void setBackboard(double backboard) { this.backboard = backboard; } public double getSteals() { return steals; } public void setSteals(double steals) { this.steals = steals; } @Override public String toString() { // TODO Auto-generated method stub return name; } }
import java.util.ArrayList; import java.util.List; import java.util.Random; public class TestMain { public static void main(String[] args) { List<Player> listPlayers=new ArrayList<Player>(); for(int i=0;i<15;i++){ Player p1=new Player(); p1.setName("afei-"+i); p1.setAssists(i); p1.setBackboard(i); //p1.setGoal(new Random(100*i).nextDouble()); p1.setGoal(i*10); p1.setSteals(i); //listPlayers.add(p1); } Player p1=new Player(); p1.setName("afei1"); p1.setGoal(1); p1.setAssists(8); listPlayers.add(p1); Player p2=new Player(); p2.setName("afei2"); p2.setGoal(2); listPlayers.add(p2); Player p3=new Player(); p3.setName("afei3"); p3.setGoal(3); listPlayers.add(p3); Player p4=new Player(); p4.setName("afei4"); p4.setGoal(7); listPlayers.add(p4); Player p5=new Player(); p5.setName("afei5"); p5.setGoal(8); listPlayers.add(p5); Player p6=new Player(); p6.setName("afei6"); p6.setGoal(25); listPlayers.add(p6); Player p7=new Player(); p7.setName("afei7"); p7.setGoal(26); listPlayers.add(p7); Player p8=new Player(); p8.setName("afei8"); p8.setGoal(27); listPlayers.add(p8); Player p9=new Player(); p9.setName("afei9"); p9.setGoal(28); listPlayers.add(p9); Kmeans<Player> kmeans = new Kmeans<Player>(listPlayers,2); List<Player>[] results = kmeans.comput(); for (int i = 0; i < results.length; i++) { System.out.println("===========类别" + (i + 1) + "================"); List<Player> list = results[i]; for (Player p : list) { System.out.println(p.getName() + "--->" + p.getGoal() + "," + p.getAssists() + "," + p.getSteals() + "," + p.getBackboard()); } } } }
源码：https://github.com/chaoren399/dkdemo/tree/master/kmeans/src