Probabilistic Classifiers

Abstract

Supervised learning is an important problem in machine learning. In this thesis, we focus on probabilistic classification based on linear models and mixture models to find the ones that are the most suitable for the given data.

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Subject(s)

Keywords: probabilistic classification, bayesian statistics, linear model, mixture model.

Citation