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)几种衡量指标。-Four kinds of clustering algorithms source code and sample code, the ultimate goal of this program is to form a set of standards for clustering, scalable tools. Including the contents of a. Clustering algorithm: Kmeans and Kmedoid algorithms, FCMclust, GKclust, GGclust algorithm 2. Assessment classified prototypes: programs can be plotted in two-dimensional image, the results of clustering 3. Verify: Program to provide an algorithm to each authentication mechanism, each clustering algorithm will calculate 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) of several metrics.

FuzzyClusteringToolbox\Demos\clusteringexamples\motorcycle\FCMcall.m
......................\.....\..................\..........\GGcall.m
......................\.....\..................\..........\GKcall.m
......................\.....\..................\..........\Kmeanscall.m
......................\.....\..................\..........\Kmedoidcall.m
......................\.....\..................\..........\MotorCycle.txt
......................\.....\..................\synthetic\FCMcall.m
......................\.....\..................\.........\GGcall.m
......................\.....\..................\.........\GKcall.m
......................\.....\..................\.........\Kmeanscall.m
......................\.....\..................\.........\Kmedoidcall.m
......................\.....\..................\.........\nDexample.m
......................\.....\......valexample\data2.txt
......................\.....\................\evalexample.m
......................\.....\.omparing\FCMcall.m
......................\.....\.........\GGcall.m
......................\.....\.........\GKcall.m
......................\.....\.........\Kmeanscall.m
......................\.....\.........\Kmedoidcall.m
......................\.....\.........\modvalidity.m
......................\.....\.........\nDexample.m
......................\.....\normexample\data3.txt
......................\.....\...........\normexample.m
......................\.....\optnumber\modvalidity.m
......................\.....\.........\MotorCycle.txt
......................\.....\.........\optnumber.m
......................\.....\PCAexample\nDexample.m
......................\.....\..........\PCAexample.m
......................\.....\projection\IRIS.MAT
......................\.....\..........\visual_call.m
......................\.....\..........\WINEDAT.TXT
......................\.....\..........\wisconsin.wk1
......................\FUZZCLUST\clusteval.m
......................\.........\clust_denormalize.m
......................\.........\clust_normalize.m
......................\.........\FCMclust.m
......................\.........\FuzSam.m
......................\.........\GGclust.m
......................\.........\GKclust.m
......................\.........\Kmeans.m
......................\.........\Kmedoid.m
......................\.........\nDexample.m
......................\.........\PCA.m
......................\.........\PROJEVAL.M
......................\.........\SAMMON.M
......................\.........\SAMSTR.M
......................\.........\validity.m
......................\FuzzyClusteringToolbox.pdf
......................\Demos\clusteringexamples\motorcycle
......................\.....\..................\synthetic
......................\.....\clusteringexamples
......................\.....\clustevalexample
......................\.....\comparing
......................\.....\normexample
......................\.....\optnumber
......................\.....\PCAexample
......................\.....\projection
......................\Demos
......................\FUZZCLUST
FuzzyClusteringToolbox

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