Mohssen Mohammed Muhammad Badruddin Khan - Machine Learning

Machine Learning

Algorithms and Applications

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Algorithms and Applications

Mohssen Mohammed

Muhammad Badruddin Khan

Eihab Bashier Mohammed Bashier

MATLAB is a trademark of The MathWorks, Inc. and is used with permission. The MathWorks does not warrant the accuracy of the text or exercises in this book. This books use or discussion of MATLAB software or related products does not constitute endorsement or sponsorship by The MathWorks of a particular pedagogical approach or particular use of the MATLAB software.

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Version Date: 20160428

International Standard Book Number-13: 978-1-4987-0538-7 (Hardback)

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Library of Congress Cataloging-in-Publication Data

Names: Mohammed, Mohssen, 1982- author. | Khan, Muhammad Badruddin, author. |

Bashier, Eihab Bashier Mohammed, author.

Title: Machine learning : algorithms and applications / Mohssen Mohammed,

Muhammad Badruddin Khan, and Eihab Bashier Mohammed Bashier.

Description: Boca Raton : CRC Press, 2017. | Includes bibliographical

references and index.

Identifiers: LCCN 2016015290 | ISBN 9781498705387 (hardcover : alk. paper)

Subjects: LCSH: Machine learning. | Computer algorithms.

Classification: LCC Q325.5 .M63 2017 | DDC 006.3/12--dc23

LC record available at https://lccn.loc.gov/2016015290

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To our parents, families, brothers and sisters, and
to our students, we dedicate this book.

If you are new to machine learning and you do not know which book to start from, then the answer is this book. If you know some of the theories in machine learning, but you do not know how to write your own algorithms, then again you should start from this book.

This book focuses on the supervised and unsupervised machine learning methods. The main objective of this book is to introduce these methods in a simple and practical way, so that they can be understood even by beginners to get benefit from them.

In each chapter, we discuss the algorithms through which the chapter methods work, and implement the algorithms in MATLAB. We chose MATLAB to be the main programming language of the book because it is simple and widely used among scientists; at the same time, it supports the machine learning methods through its statistics toolbox.

The book consists of 12 chapters, divided into two sections:

I: Supervised Learning Algorithms

II: Unsupervised Learning Algorithms

In the first section, we discuss the decision trees, rule-based classifiers, nave Bayes classification, k-nearest neighbors, neural networks, linear discriminant analysis, and support vector machines.

In the second section, we discuss the k-means, Gaussian mixture model, hidden Markov model, and principal component analysis in the context of dimensionality reduction.

We have written the chapters in such a way that all are independent of one another. That means the reader can start from any chapter and understand it easily.

MATLAB is a registered trademark of The MathWorks, Inc. For product information, please contact:

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