Meet the editor

Dr. Derya Birant received a BS, MS, and Ph.D. in Computer Engineering from Dokuz Eylul University, Turkey in 2000, 2002, and 2006, respectively. Since 2017, she has been an Associate Professor at the Computer Engineering Department of Dokuz Eylul University. She is also the vice-chair of the department. She was a Visiting Lecturer at South East European University in 2006 and Ege University between 2010 and 2012. Her research

interests include data mining and machine learning. She is the author of six book chapters and more than seventy publications. Dr. Birant has supervised more than thirty Ph.D. and MSc students. She has been involved in more than twenty longterm interdisciplinary R&D projects on data mining.

Contents

and Computer Vision

*by Bouchra Lamrini*

*and Oya Kalipsiz*

Jungle Method *by Derya Birant*

in Machine Learning

*by Esma Ergüner Özkoç*

*and Molibeli Benedict Taele*

*by Elife Ozturk Kiyak*

Clustering of Time-Series Data

*and Subarna Roy*

*by Selma Tekir and Yalin Bastanlar*

Association Rule Mining on Big Data Sets

**Preface XI**

**Chapter 1 1**

**Chapter 2 21**

**Chapter 3 43**

**Chapter 4 55**

**Chapter 5 67**

**Chapter 6 87**

**Chapter 7 107**

**Chapter 8 119**

Deep Learning: Exemplar Studies in Natural Language Processing

Contribution to Decision Tree Induction with Python: A Review

*by Oguz Celik, Muruvvet Hasanbasoglu, Mehmet S. Aktas*

Data Mining in Banking Sector Using Weighted Decision

*by Pramod Kumar, Sameer Ambekar, Manish Kumar*

Weather Nowcasting Using Deep Learning Techniques

Data Mining and Machine Learning for Software Engineering

*by Makhamisa Senekane, Mhlambululi Mafu*

Analytical Statistics Techniques of Classification and Regression

## Contents



Preface

Data mining is a branch of computer science that is used to automatically extract meaningful, useful knowledge and previously unknown, hidden, interesting patterns from a large amount of data to support the decision-making process.

This book presents recent theoretical and practical advances in the field of data mining. It reports on a number of data mining methods, including *classification*,

This book brings together many different successful data mining studies in various areas such as health, banking, education, software engineering, animal science, and the environment. The goal is to help data miners, researchers, academics, and scientists who wish to apply data mining techniques in their studies. The references

The main strength of the book is the wealth of the case studies contained within. Chapters cover a number of innovative and recently developed data mining applications. Another important feature of the book is the clear introduction and

The authors of this book have been actively working in the data mining field for years and thus have a lot of experience. They have the skills, knowledge, and expertise needed to share with us about real-world data mining applications. They have aimed at providing readers with a comprehensive understanding of data mining methods and thus present research results in various domains from

different points of view. They explain the fundamental data mining techniques for

It was not possible for me to accomplish this book without the outstanding contributions of many people. I would like to thank the contributing authors for their excellent works. Much appreciation goes to them for the time and effort they put in. I would also like to thank my husband for his love and support during the editing of this book. I also extend many thanks to Lada Bozic and Marijana Francetic

for facilitating administrative matters. Finally, I express my gratitude to the publisher, IntechOpen, for giving me the opportunity to complete this book.

> **Dr. Derya Birant** Associate Professor, Dokuz Eylül University,

> > Turkey

Department of Computer Engineering,

I hope you enjoy reading this book as much as I enjoyed editing it.

*clustering*, and *association rule mining*.

extracting information from a large dataset.

collected in this book may be used as further reading lists.

background information provided at the beginning of each chapter.
