Description: CVAP includes 4 External validity indices, 14 Internal validity indices and 5 clustering algorithms (K-means, PAM, hierarchical clustering, SOM and etc.). It supports other clustering algorithms via loading a solution file with class labels, or by adding new codes. And similarity metrics of Euclidean distance and Pearson correlation coefficient are supported.
File list (Check if you may need any files):
agg_hierarchical.m
Copyright.txt
CVAP-examples.pdf
daisy.m
daisyc.dll
datafile
........\iris-solution.txt
........\iris.txt
........\leuk72_3k.txt
data_normalization.m
find_nearpoint.m
ind2cluster.m
License_Netlab.txt
mainCVAP.fig
mainCVAP.m
mainCVAP6.fig
mainCVAP6.m
neural_gas.m
pam.m
pamc.dll
pca_of_data.m
plot_data_bylabels.m
Readme.txt
show2dim_byclass.m
similarity_euclid.m
similarity_pearson.m
similarity_pearsonC.m
som.m
somtrain.m
som_netlab.m
valid_clear_clustering.m
valid_clear_plotting.m
valid_clear_validation.m
valid_clusteringAlgs.m
valid_data_load.m
valid_data_plot.m
valid_data_plot_check.m
valid_data_split.m
valid_DbDunn.m
valid_errorate.m
valid_errorate_check.m
valid_external.m
valid_findk.m
valid_hierarchical.m
valid_internal.m
valid_internal_deviation.m
valid_internal_intra.m
valid_intrainter.m
valid_mutiple_validation.m
valid_plot_hierarchytree.m
valid_plot_index.m
valid_print_label.m
valid_redraw.m
valid_runclustering.m
valid_runvalidation.m
valid_sapcluster.m
valid_save_solution.m
valid_solution_load.m
valid_sumpearson.m
valid_sumsqures.m
valid_validation_check.m
xlim2.m
Download