zoukankan      html  css  js  c++  java
  • 调用WEKA包进行kmeans聚类(java)

    所用数据文件:data1.txt

    @RELATION data1
    
    
    @ATTRIBUTE one REAL
    @ATTRIBUTE two REAL
    
    
    
    
    @DATA
    0.184000 0.482000
    0.152000 0.540000
    0.152000 0.596000
    0.178000 0.626000
    0.206000 0.598000
    0.230000 0.562000
    0.224000 0.524000
    0.204000 0.540000
    0.190000 0.572000
    0.216000 0.608000
    0.240000 0.626000
    0.256000 0.584000
    0.272000 0.546000
    0.234000 0.468000
    0.222000 0.490000
    0.214000 0.414000
    0.252000 0.336000
    0.298000 0.336000
    0.316000 0.376000
    0.318000 0.434000
    0.308000 0.480000
    0.272000 0.408000
    0.272000 0.462000
    0.280000 0.524000
    0.296000 0.544000
    0.340000 0.534000
    0.346000 0.422000
    0.354000 0.356000
    0.160000 0.282000
    0.160000 0.282000
    0.156000 0.398000
    0.138000 0.466000
    0.154000 0.442000
    0.180000 0.334000
    0.184000 0.300000
    0.684000 0.420000
    0.678000 0.494000
    0.710000 0.592000
    0.716000 0.508000
    0.744000 0.528000
    0.716000 0.540000
    0.692000 0.540000
    0.696000 0.494000
    0.722000 0.466000
    0.738000 0.474000
    0.746000 0.484000
    0.750000 0.500000
    0.746000 0.440000
    0.718000 0.446000
    0.692000 0.466000
    0.746000 0.418000
    0.768000 0.460000
    0.272000 0.290000
    0.240000 0.376000
    0.212000 0.410000
    0.154000 0.564000
    0.252000 0.704000
    0.298000 0.714000
    0.314000 0.668000
    0.326000 0.566000
    0.344000 0.468000
    0.324000 0.632000
    0.164000 0.688000
    0.216000 0.684000
    0.392000 0.682000
    0.392000 0.628000
    0.392000 0.518000
    0.398000 0.502000
    0.392000 0.364000
    0.360000 0.308000
    0.326000 0.308000
    0.402000 0.342000
    0.404000 0.418000
    0.634000 0.458000
    0.650000 0.378000
    0.698000 0.348000
    0.732000 0.350000
    0.766000 0.364000
    0.800000 0.388000
    0.808000 0.428000
    0.826000 0.466000
    0.842000 0.510000
    0.842000 0.556000
    0.830000 0.594000
    0.772000 0.646000
    0.708000 0.654000
    0.632000 0.640000
    0.628000 0.564000
    0.624000 0.352000
    0.650000 0.286000
    0.694000 0.242000
    0.732000 0.214000
    0.832000 0.214000
    0.832000 0.264000
    0.796000 0.280000
    0.778000 0.288000
    0.770000 0.294000
    0.892000 0.342000
    0.910000 0.366000
    0.910000 0.394000
    0.872000 0.382000
    0.774000 0.314000
    0.718000 0.252000
    0.688000 0.284000
    0.648000 0.322000
    0.602000 0.460000
    0.596000 0.496000
    0.570000 0.550000
    0.564000 0.592000
    0.574000 0.624000
    0.582000 0.644000
    0.596000 0.664000
    0.662000 0.704000
    0.692000 0.722000
    0.710000 0.736000
    0.848000 0.732000
    0.888000 0.686000
    0.924000 0.514000
    0.914000 0.470000
    0.880000 0.492000
    0.848000 0.706000
    0.730000 0.736000
    0.676000 0.734000
    0.628000 0.732000
    0.782000 0.708000
    0.806000 0.674000
    0.830000 0.630000
    0.564000 0.730000
    0.554000 0.538000
    0.570000 0.502000
    0.572000 0.432000
    0.590000 0.356000
    0.652000 0.232000
    0.676000 0.178000
    0.684000 0.152000
    0.728000 0.172000
    0.758000 0.148000
    0.864000 0.176000
    0.646000 0.242000
    0.638000 0.254000
    0.766000 0.276000
    0.882000 0.278000
    0.900000 0.278000
    0.906000 0.302000
    0.892000 0.316000
    0.570000 0.324000
    0.798000 0.150000
    0.832000 0.114000
    0.714000 0.156000
    0.648000 0.154000
    0.644000 0.212000
    0.642000 0.250000
    0.658000 0.284000
    0.710000 0.296000
    0.794000 0.288000
    0.846000 0.260000
    0.856000 0.304000
    0.858000 0.392000
    0.858000 0.476000
    0.778000 0.640000
    0.736000 0.662000
    0.718000 0.690000
    0.634000 0.692000
    0.596000 0.710000
    0.570000 0.720000
    0.554000 0.732000
    0.548000 0.686000
    0.524000 0.740000
    0.598000 0.768000
    0.660000 0.796000
    

    前言:Kmeans是一种非常经典的聚类算法。它利用簇的中心到对象的距离来分配每个对象的簇所属关系。同时迭代的进行簇的中心的更新以及簇分配的更新,直到收敛。


    下面是调用weka包中实现的kmeans的代码


    package others;
    
    import java.io.File;
    
    import weka.clusterers.SimpleKMeans;
    import weka.core.DistanceFunction;
    import weka.core.Instances;
    import weka.core.converters.ArffLoader;
    
    public class ArrayListTest {
    
    	public static void main(String[] args){
    		Instances ins = null;
    		
    		SimpleKMeans KM = null;
    		DistanceFunction disFun = null;
    		
    		try {
    			// 读入样本数据
    			File file = new File("data/data1.txt");
    			ArffLoader loader = new ArffLoader();
    			loader.setFile(file);
    			ins = loader.getDataSet();
    			
    			// 初始化聚类器 (加载算法)
    			KM = new SimpleKMeans();
    			KM.setNumClusters(4); 		//设置聚类要得到的类别数量
    			KM.buildClusterer(ins);		//开始进行聚类
    			System.out.println(KM.preserveInstancesOrderTipText());
    			// 打印聚类结果
    			System.out.println(KM.toString());
    			
    		} catch(Exception e) {
    			e.printStackTrace();
    		}
    	}
    }




  • 相关阅读:
    声明以及字符表述类--字母大小写的敏感性
    条款52:写了placement new 也要写placement delete(write placement delete if you write placement new)
    verdi知识点
    关于$test$plusargs和$value$plusargs的小结
    条款40:明智而审慎地使用多重继承(use multiple inheritance judiciously)
    条款39:明智而审慎地使用private继承(use private inheritance judiciously)
    条款38:通过复合塑模has-a或“根据某物实现出”
    条款37:绝不重新定义继承而来的缺省参数值(Never redefine a function's inherited default parameter value)
    自学nodejs系列
    五个典型的JavaScript面试题
  • 原文地址:https://www.cnblogs.com/wenbaoli/p/5655747.html
Copyright © 2011-2022 走看看