Introduction Icasso is based on running FastICA several times (resampling). Icasso pools all the estimates together and forms clusters bottom-up among them. The basic idea is that a tight cluster of estimates is considered to be a candidate for including a "good" estimate. A centroid of such cluster is considered a more reliable estimates than any estimate from an arbitrary run. (Instead of an average as a centroid, Icasso visualizes and returns a centrotype from each cluster. This is the one of the original estimates that is most similar to other estimates in the same cluster. You can compute the average by using Icasso functions.)

icasso122
.........\cca.m
.........\centrotype.m
.........\clusterhull.m
.........\clusterquality.m
.........\clusterstat.m
.........\corrw.m
.........\hcluster.m
.........\icasso.m
.........\icassoCluster.m
.........\icassoDendrogram.m
.........\icassoEst.m
.........\icassoExp.m
.........\icassoGet.m
.........\icassoGraph.m
.........\icassoIdx2Centrotype.m
.........\icassoProjection.m
.........\icassoResult.m
.........\icassoRindex.m
.........\icassoShow.m
.........\icassoStability.m
.........\icassoStruct.m
.........\megdata.mat
.........\megdemo.m
.........\mmds.m
.........\parallelize.m
.........\processvarargin.m
.........\README_license.txt
.........\redscale.m
.........\reducesim.m
.........\rindex.m
.........\sammon.m
.........\signalplot.m
.........\sim2dis.m
.........\similaritygraph.m
.........\som_dendrogram.m
.........\som_grid.m
.........\som_linkage.m
.........\som_set.m
.........\sqrtsim2dis.m
.........\vis_valuetype.m

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