这次上传的代码是关于K-means Clusters的代码，希望能对大家有用。
上传时间： 2013-12-15
上传用户：lindor
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
The last step in training phase is refinement of the Clusters found above. Although DynamicClustering counters all the basic k-means disadvantages, setting the intra-cluster similarity r may require experimentation. Also, a cluster may have a lot in common with another, i.e., sequences assigned to it are as close to it as they are to another cluster. There may also be denser sub-Clusters within the larger ones.
标签： DynamicClusteri refinement Although Clusters
上传时间： 2014-01-04
上传用户：watch100
Determination of number of Clusters in K-Means Clustering and Application in color image segmenta
标签： Determination Application Clustering Clusters
上传时间： 2013-12-05
上传用户：zsjzc
High.Performance.Linux.Clusters.With.Oscar.Rocks.openmosix.And.Mpi.2004--介绍linux集群的好书（英文版），希望大家喜欢
标签： Performance openmosix Clusters Linux
上传时间： 2016-10-09
上传用户：gyq
clustering matlab code,check the number of Clusters alive at certain iterations
标签： clustering iterations Clusters certain
上传时间： 2013-12-15
上传用户：亚亚娟娟123
To identify distinguishable Clusters of data in an n-dimensional pixel value image. Given: Samples of multi-spectral satellite images
标签： distinguishable n-dimensional identify Clusters
上传时间： 2017-08-08
上传用户：it男一枚
function [Clusters,c,F]=fisher_classify(A,B,data) fisher判别法程序 输入A、B为已知类别样本的样本-变量矩阵，data为待分类样本 输出C为判别系数向量
标签： fisher_classify function Clusters fisher
上传时间： 2013-12-19
上传用户：CHINA526
My version of k-means function. Improved so that there are no empty Clusters after segmentation.
标签： segmentation Improved function Clusters
上传时间： 2013-12-24
上传用户：hoperingcong
二维的DBSCAN聚类算法，输入（x,y）数组，搜索半径Eps，密度搜索参数Minpts。输出: Clusters，每一行代表一个簇，形式为簇的对象对应的原数据集的ID
上传时间： 2015-06-01
上传用户：sy_jiadeyi
