Discriminant Analysis
Gilles Celeux
In: Data Analysis (2009) Hermès , Paris .

Abstract

This chapter gives a tutorial of the main methods of Discriminant analysis (Linear Discriminant Analysis, Logistic Regression, k nearest neighbors, Classification trees, Neural Networks), the main tasks of a discriminant analysis (variable selection, assessing the error rate) and give insights on new methods of classification (Kernel methods, Boosting, regularization...)

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