3.聚类–K-means的Java实现
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 {
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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;
} }.csharpcode, .csharpcode pre
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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;
}
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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());
}
} } }.csharpcode, .csharpcode pre
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源码：https://github.com/chaoren399/dkdemo/tree/master/kmeans/src
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