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
高斯分布期望优化（em）算法matlab实现，流量矩阵模型
上传时间： 2013-12-10
上传用户：思琦琦
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
二维涡流位置及流场分布计算程序，Vortex Panel Method
上传时间： 2016-02-21
上传用户：qilin
K-MEANS算法程序(MATLAB环境)
上传时间： 2014-07-11
上传用户：JasonC
个时频原子的模糊函数及理想时频分布；三个时频原子的理想时频分布
上传时间： 2016-02-25
上传用户：chenbhdt
Linux Server Hacks, Volume Two By Brian K. Jones, William von Hagen ............................................... Publisher: O Reilly Pub Date: December 2005 Print ISBN-10: 0-596-10082-5 Print ISBN-13: 978-0-59-610082-7 Pages: 478
上传时间： 2016-02-26
上传用户：ZJX5201314
加权k均值算法，或者称为加权C均值聚类算法
上传时间： 2016-02-26
上传用户：TF2015
