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Validation of Archetypal Analysis
Event Title
The 2017 International conference on Fuzzy Systems - FUZZ-IEEE 2017
Year (definitive publication)
2017
Language
English
Country
Italy
More Information
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Abstract
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%.
Acknowledgements
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Keywords
Fields of Science and Technology Classification
- Physical Sciences - Natural Sciences
