Data Mining : Techniques And Trends

Data Mining : Techniques And Trends

( 52 )
Sold ( 52 times )
5695 Views

This product is currently not available.

Save extra with 1 Offers

Get ₹ 50

Instant Cashback on the purchase of ₹ 400 or above

Product Specifications

Publisher PHI Learning All Computer Science books by PHI Learning
ISBN 9788120338128
Author: SIVASELVAN, B. , GOPALAN, N. P.
Number of Pages 144
Available
Available in all digital devices
  • Snapshot
  • About the book
  • Sample book
Data Mining : Techniques And Trends - Page 1 Data Mining : Techniques And Trends - Page 2 Data Mining : Techniques And Trends - Page 3 Data Mining : Techniques And Trends - Page 4 Data Mining : Techniques And Trends - Page 5

About The Book Data Mining

Book Summary:

In todays world of competitive business environment, there is a driving need to extract hidden and potentially meaningful information from large databases for effective decision making. This compact book explores the concept of data mining and discusses various data mining techniques and their applications. It is primarily designed for the students of Computer Science and Engineering, Information Technology, Computer Applications, and Management.

Written in a student-friendly style, the book describes the various phases of data mining, architecture of a data mining system, and the types of knowledge that can be mined from databases. It elaborates on different data preprocessing techniques such as cleaning, integration, transformation and reduction. The text then explains the various data mining techniques such as association rule mining, data classification and clustering. The book adopts an algorithm-centric approach presenting various algorithms for these data mining techniques. Finally, the text ends with an exhaustive discussion on multimedia data mining (MDM).

Key Features :

Illustrates the concepts with the help of various figures and examples.

Provides a summary at the end of each chapter for quick revision of key points.

Offers chapter-end questions for self-evaluation.


Table of Contents:
contents
Preface
1. INTRODUCTION TO DATA MINING
2. DATA PREPROCESSING TECHNIQUE
3. ASSOCIATION RULE MINING
4. DATA CLASSIFICATION TECHNIQUES
5. DATA CLUSTERING
6. OTHER DATA MINING TECHNIQUES
7. MULTIMEDIA DATA MINING: THE RECENT TREND
Index