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Publication Detailed Description
On ill-conceived initialization in archetypal analysis
Journal Title
Advances in Data Analysis and Classification
Year (definitive publication)
2017
Language
English
Country
Germany
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Abstract
We show that an improper initialization of the matrix of prototypes, V, can be misleading, and potentially gives rise to a degenerate fuzzy partition when performing fuzzy clustering by means of an archetypal analysis. Subsequently, we propose an algorithm to correct the initial guess for V, which is grounded in two theoretical results on convex hulls. A numerical experiment carried out to assess its accuracy, and involving more than 200,000 initializations, shows a failure rate of below 0.8%.
Acknowledgements
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Keywords
Matrix factorization,Fuzzy clustering,Archetypal analysis,Initialization,Polytopes
Fields of Science and Technology Classification
- Mathematics - Natural Sciences
