Introduction to Data Mining and Soft Computing Techniques
- 4h 44m
- M. Ramakrishna Murthy
- Laxmi Publications
- 2015
Data Mining and Softcomputing is the fastest growing technology for the business world. The collection of data, whether their origin is business or scientific experiment, has recently spread a tremendous interest in the area of knowledge discovery or data mining with help of softcomputing.
Data mining, also popularly referred to as Knowledge Discovery in Databases (KDD), is a process of finding value from volume. It is a multidisciplinary field, using ideas from database technology, machine learning, Artificial Intelligence, Neural networks, statistics, pattern recognition, information retrieval etc. Softcomputing is the useful technology to improve performance of the discovery process.
This book is of immense use for students of B.Tech(CSE), B.Tech(IT), MCA and M.Tech, software professionals, researchers and all others who are involved in this field.
This book is arranged into 11 chapters. At the end of each chapter summary of the chapter and review questions are provided and at the end of the book multiple choice questions of all chapters are given for the benefit of the students.
About the Author
M. Ramakrishna Murthy is currently working as an Associate Professor in the Department of Computer Sciences & Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh. He has completed M.Tech (CS&T) from Andhra University and currently pursuing Ph.D. from JNTU Hyderabad. He has been teaching for the last 15 years in various capacities. Around 20 research articles are there till now in his credit in different international journals and conferences. His research interests include data mining, text mining and evolutionary computing.
In this Book
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Introduction
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Data Mining
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Data Warehouse
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Data Preprocessing
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Data Mining Primitives and DMQL
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Association Rules Mining
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Classification
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Cluster Analysis
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Data Mining for Unstructured Types of Data
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Introduction to Soft Computing Techniques
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Artificial Neural Networks
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References
