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K_MEANS
- 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 u
200412262259022
- k-meansy算法源代码。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 clu
kmeans
- kmeans算法实现 a simple k-means clustering routine. returns the cluster labels of the data points in an array.
mopsoGECCO.tar
- 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
wawatextcluster
- 蛙蛙的中文文本聚类，主要采用k-means算法。wawa s text cluster using C#.
新建 Microsoft Word 文档 (3)
- 基于划分的聚类分析算法k-means,主要用于数据挖掘领域.-Partition - based cluster analysis algorithm k-means, used mainly for data mining areas.
texture-gabor.rar
- gabor提取纹理特征，k-means方法无监督聚类进行图像分割,extract texture feature, cluster by k-means
MATLAB
- 编写的粒子群(PSO)算法优化Kmeans聚类的MATLAB代码，MATLAB6.5/7.1测试通过，其它版本没测试。-(PSO)Kmeans MATLAB6.5/7.1
my-keans
- 实现聚类算法中的K-MEANS算法，对随机生成的点进行了聚类。-Clustering algorithm to achieve the K-MEANS algorithm, on randomly generated points in the cluster.
KMEANS10
- The k-means algorithm is an algorithm to cluster n objects based on attributes into k partitions, k < n. It is similar to the expectation-maximization algorithm for mixtures of Gaussians in that they both attempt to find the centers of natural clu
unsupervisedClassification
- 非监督分类程序，MATLAB环境，采用K均值算法，通过初始聚类中心逐次迭代而得到所要分类，并输出分类后的图像。-Non-supervised classification procedures, MATLAB environment, using K-means algorithm, the initial cluster center through successive iterations to be classified, and the output classification im
kmean
- k-means 算法的工作过程说明如下：首先从n个数据对象任意选择 k 个对象作为初始聚类中心；而对于所剩下其它对象，则根据它们与这些聚类中心的相似度（距离），分别将它们分配给与其最相似的（聚类中心所代表的）聚类；然后再计算每个所获新聚类的聚类中心（该聚类中所有对象的均值）；不断重复这一过程直到标准测度函数开始收敛为止。-k-means algorithm process as follows: First of all, the object data from the n choose k
SimpleKMeans
- k-means聚类算法 指定类别数为K，对样本集合进行聚类，聚类的结果由K 个聚类中心来表达，基于给定的聚类目标函数(或者说是聚类效果判别准则)，算法采用迭代更新的方法，每一次迭代过程都是向目标函数值减小的方向进行，最终的聚类结果使目标函数值取得极小值，达到较优的聚类效果。-k-means clustering algorithm for specific classes of K, the collection of samples for clustering, clustering t
KMEANS
- 基于c++的k-means聚类分析算法，实用性很强-Cluster analysis algorithm
ClusteringToolbox
- 用于进行聚类分析的matlab工具箱，包括K-means、模糊聚类等。-Used for cluster analysis of the matlab toolbox.
xuzhuol
- 基于改进K-means的压缩IP 由于k-means本身受异常点影响较大，这里采用迭代k-means的方法，降低异常点的影响，减少计算量和提高聚类数目的灵活性。并添加合并异常聚类方法，提高聚类的均匀性-K-means based on improved compression IP As k-means itself is influenced by outliers, where an iterative k-means method to reduce the impact of o
k_means
- k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。-In statistics and machine learning, k-means clustering is a method of cluster analysis which aims to partition n observations into
KMEANS
- 实现k均值聚类算，输出聚类中心和聚类后的分组结果-To achieve k-means clustering calculation, the output cluster centers and cluster grouping of the results of post-
k_means
- K-means algorithm in C++ user pre-defined cluster number input file of data points output file of final best centroids
KmeansAlgorithm
- 实现k均值聚类算法，本算法可以随机设置初始测试集，也可以随机选取初始类。-K means algorithm The algorithm can set intial data set randomly。also can randomly choice initial data cluster