PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Patch Learning for Incremental Classifier Design
R Sicard, T Artières and E Petit
In: ECAI 2006, 28 Aug - 01 Sept, Italy.

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We present a learning algorithm for nominal data. It builds a classifier by adding iteratively a simple patch function that modifies the current classifier. Its main advantage lies in the possibility to learn every patch function parameters optimally from the Bayesian point of view hence avoiding overtraining.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:2835
Deposited By:Thierry Artieres
Deposited On:22 November 2006

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