Introduction to Data Mining and Softcomputing Techniques

Introduction to Data Mining and Softcomputing Techniques
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Introduction to Data Mining and Softcomputing Techniques

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Publisher: Laxmi Publications
ISBN: 9789383828401
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PREFACE 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. Chapter 1 This chapter introduces basic concepts of databases, foundations of data mining and evolution of data mining. Chapter 2 In this chapter the topics covered include data mining process, architecture, functionalities and classification of data mining system. All the applications of Data mining are also covered. Chapter 3 Data warehousing is the important concept related to the data mining. In this chapter data warehousing development and implementation technology, OLAP and OLTP technologies are covered. Chapter 4 Data preprocessing is an essential part of work to improve the efficiency and ease of the data miming process. In this chapter data preprocessing issues are discussed like data cleaning, data integration, data transformation and data reduction. Chapter 5 The primitives of data mining systems allow the users to interactively communicate with the data mining system during discovered in order to examine the findings from different angles or depth and direct the data mining process. In this chapter the above issues are discussed in easy manner and also emphasis is given on DMQL Data Mining Query Language . Chapter 6 In this chapter emphasis is given on association rule mining, which is a important functionality of data mining for market basket analysis. Apriori and FP-tree methods are discussed with interesting examples for easy understanding. Chapter 7 This chapter has given basic idea of the classification techniques in data mining. The classification problem tends to occur in a wide variety of areas. This wide spread need for classification has led to the development of many different classification techniques.
vi Introduction to Data Mining and Soft Computing Techniques Chapter 8 Cluster Analysis is emphasized in this chapter. Eight kinds of clustering algorithms have been discussed in easy and understandable manner and outlier analysis is introduced. At the end of the chapter comparison of all clustering algorithms in time and space complexity point of view is given. Chapter 9 This chapter has given data mining techniques for complex types of data including spatial data, multimedia data, time series data, text data and the World Wide Web. Chapter 10 and 11 present various softcomputing techniques. Particularly in the chapter 10 softcomputing techniques like evolutionary computing, genetic algorithms and machine learning are introduced. In chapter 11 basic concepts of artificial neural networks and its applications are discussed. Author
ACKNOWLEDGEMENTS Guru bramha guru Vishnu guru devo maheswara guru saksatu para bramha tasmai sri