模式识别算法 k均值和感知器算法的具体实现实例
上传时间： 2014-01-20
上传用户：stella2015
自己花费整整两个星期写出来的关于数据挖掘K-means算法的论文，论文中详细的进行了论述并提出了改进后的算法以及对比欢迎下载
上传时间： 2016-01-25
上传用户：时代电子小智
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标签： lvbfdghfdhxfgjhkh gfjhgljl jhkjo vbn
上传时间： 2016-01-25
上传用户：450976175
This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the screen.
标签： code implementing directory algorithm
上传时间： 2014-01-15
上传用户：woshini123456
k-means是一种经典的聚类算法，这是用java实现k-means的源码，其中包括了测试数据文件
上传时间： 2014-01-11
上传用户：lizhizheng88
模式识别中K均值算法的示例程序，可对一组数据分类并图形输出分类结果。
上传时间： 2013-12-23
上传用户：yph853211
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
标签： the decision clusters Cluster
上传时间： 2013-12-21
上传用户：gxmm
主要是KNN（the k-nearest neighbor algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface mapping）算法。 and a simple clustering algorithm.
标签： quantization k-nearest algorithm decision
上传时间： 2016-02-07
上传用户：zhyiroy
这是一个关于K均值的聚类算法希望对大家有用
上传时间： 2016-02-15
上传用户：ma1301115706
选择第k小的元素，c语言 partition 要好好看看 理解函数意思
标签： 元素
上传时间： 2016-02-19
上传用户：ukuk
