Author(s): Suleman, A.
Date: 2017
Origin: Repositório ISCTE
Subject(s): Fuzzy clustering; Archetypal analysis; Validation index
Document details
Validation of archetypal analysis
Description
We use an information-theoretic criterion to assess the goodness-of-fit of the output of archetypal analysis (AA), also intended as a fuzzy clustering tool. It is an adaptation of an existing AIC-like measure to the specifics of AA. We test its effectiveness using artificial data and some data sets arising from real life problems. In most cases, the results achieved are similar to those provided by an external similarity index. The average reconstruction accuracy is about 93%.
Document Type
Conference object
Language English
Language English
