Data Mining and Data Warehousing: Principles and Practical Techniques
Authors: Parteek Bhatia
ISBN-10: 1108727743
ISBN-13: 9781108727747
Released: 2019-06-27
Print Length 页数: 506 pages
Book Description
Written in lucid language,this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory,decision tree,Naïve Bayes classifier,distance metrics,partitioning clustering,associate mining,data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science,engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification,associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics,relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.
Contents
Figures
Tables
Preface
Acknowledgments
1Beainning with Machine Learning
2Introduction to Data Mining
3Beginning with Weka and R Language
4Data Preprocessing
5Classification
6 Implementing Classification in Weka and R
7 Cluster Analysis
8 Implementing Clustering with Weka and R
9 Association Mining
10lmplementing Association Mining with Weka and R
11Web Mining and Search Engines
12Data Warehouse
13Data Warehouse Schema
14Online Analytical Processing
15Big Data and NoSQL
Index
Colour Plates
