Canonical k-Means Clustering for Functional Data
نویسندگان
چکیده
Thaddeus Tarpey and Eva Petkova 1 Department Mathematics and Statistics, Wright State University, Dayton, Ohio 45435, [email protected]. 2 Department of Child and Adolescent Psychiatry, New York University, New York, NY 10016-6023 Abstract Cluster analysis is a powerful tool for discovering sources of heterogeneity in data. However, clinically interesting sources of heterogeneity, such as placebo-effects or specific drug effects may be swamped out by other sources of variability in the data which can cause a distribution to deviate from normality. This paper proposes linearly transforming the data before clustering. An example of this is a canonical type transformation to maximize between cluster variability relative to within cluster variability.
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