matlab聚类kmeans代码-hadoop-hw7:hadoop-hw7
matlab聚类kmeans代码
作业7
要求
在MapReduce上实现K-Means算法并在小数据集上测试。可以使用附件的数据集，也可以随机生成若干散点的二维数据（x,
y)。设置不同的K值和迭代次数，可视化聚类结果。
提交要求同作业5，附上可视化截图。
实现思路
我直接使用了实例代码来运行，用原来的代码创建maven项目KMeansExample。由于原来的代码不是用maven管理的，而且是基于Hadoop1.2编写的程序，所以有一些地方需要进行小小的修改。比如每个java文件前面都要加上对应的包名称，Job对象的创建需要调用getInstance静态方法，而不能直接new
Job。
我尝试研读了整个算法的代码，下面简要描述一下示例代码的思路。
主程序：KMeansDriver.main()
KMeansDriver.main()方法是整个算法的主程序，它从命令行接收指定的参数k（需要聚成的类数），iterationNum（迭代次数），inputpath，outputpath。依次调用三个主要的过程：
generateInitialCluster()：随机产生k个cluster
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