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.

There is a more recent version of this eprint available. Click here to view it.

Abstract

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.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
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

Available Versions of this Item