cluster analysis - Variable selection for k-means clustering -



cluster analysis - Variable selection for k-means clustering -

i'm wondering if there methods selecting variables k-means algorithm. trying market segmentation using algorithm , have dataset dozens of potential variables. have results easy interpret, should limit number of variables max. 5-6. particularly interested in solutions can implemented in spss statistics or weka. also, there method/algorithm getting optimal number of variables clustering (i.e. how many of 'good' variables should use)?

try factor analysis, should help. no. of factors utilize depend on number of variables having eigen value >= 1. after finding no of factors, utilize fa() function find loadings value , decide variables need maintain , discard. help in removing highly multicollinear variables.

cluster-analysis data-mining weka k-means spss

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