Perceptron sous forme duale tronquée et variantes

Authors: Rouleau, Christian
Advisor: Marchand, Mario
Abstract: Machine Learning is a part of the artificial intelligence and is used in many fields in science. It is divided into three categories : supervised, not supervised and by reinforcement. This master’s paper will relate only the supervised learning and more precisely the classification of datas. One of the first algorithms in classification, the perceptron, was proposed in the Sixties. We propose an alternative of this algorithm, which we call the truncated dual perceptron, which allows the stop of the algorithm according to a new criterion. We will compare this new alternative with other alternatives of the perceptron. Moreover, we will use the truncated dual perceptron to build more complex classifiers like the «Bayes Point Machines».
Document Type: Mémoire de maîtrise
Issue Date: 2007
Open Access Date: 12 April 2018
Permalink: http://hdl.handle.net/20.500.11794/19078
Grantor: Université Laval
Collection:Thèses et mémoires

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