(模糊聚类和数据分析工具箱)

建不了的模。

(模糊聚类和数据分析工具箱)  

The Fuzzy Clustering and Data Analysis Toolbox is a collection of MATLAB functions. The toolbox provides five categories of functions:  

- Clustering algorithms. These functions group the given data set into clusters by different approaches: functions Kmeans and Kmedoid  
are hard partitioning methods, FCMclust, GKclust, GGclust are fuzzy partitioning methods with different distance norms.  

- Evaluation with cluster prototypes. On the score of the clustering results of a data set there is a possibility to calculate membership for "unseen" data sets with these set of functions. In 2-dimensional case the functions draw a contour-map in the data space to visualize  
the results.  

- Validation. The validity function provides cluster validity measures for each partition. It is useful when the number of cluster is unknown a priori. The optimal partition can be determined by the point of the extrema of the validation indexes in dependence of the number of clusters. The indexes calculated are: Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), Separation Index (S), Xie and Beni's Index (XB), Dunn's Index (DI) and Alternative Dunn Index (DII).  

- Visualization. The Visualization part of this toolbox provides the modified Sammon mapping of the data. This mapping method is a  
multidimensional scaling method described by Sammon.  

- Examples. An example based on industrial data set to present the usefulness of these toolbox and algorithms.

游客，如果您要查看本帖隐藏内容请回复

wwwshmily

xxxxxxxxxxxxx

95778472

学习一下

凯鲁嘎吉

~~~~~~~~~~~~~~~~~~~~~~·

凯鲁嘎吉

~~~~~~~~~~~~~~~~~~~~~~·

guozhi520

回复回复

spiderwoman

好好看看。。。。。。。。。。。。。。。。。

bo707977656

轨道是规范化和发动机

hutaobetter

没看太明白，是啥啊

唐甜小甜

想看~~~~~~~~~~~~~~~~~~