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Machine Learning
book

Machine Learning

by Mohssen Mohammed, Muhammad Badruddin Khan, Eihab Mohammed Bashier
August 2016
Intermediate to advanced content levelIntermediate to advanced
204 pages
3h 51m
English
CRC Press
Content preview from Machine Learning

Chapter 7

Linear Discriminant Analysis

7.1 Introduction

In 1936, statistical pioneer Ronald Fisher discussed linear discriminant [1] that became a common method to be used in statistics, pattern recognition, and machine learning. The idea was to find a linear combination of features that are able to separate two or more classes. The resulting linear combination can also be used for dimensionality reduction. Linear discriminant analysis (LDA) is a generalization of the Fisher linear discriminant.

This method was used to explain the bankruptcy or survival of the firm [2]. In face recognition problems, it is used to reduce dimensions.

LDA seeks to maximize class discrimination and produces exactly as many linear functions as there are classes. ...

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Publisher Resources

ISBN: 9781315354415