Data Mining and Data Warehousing: Principles and Practical Techniques

Data Mining and Data Warehousing: Principles and Practical Techniques

Computers & Technology
ISBN: 1108727743 Format: PDF Edition: - Date: May 31, 2019 Pages: 600 pages Language: English

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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.

Content

Chapter 1. Beginning with Machine Learning
Chapter 2. Introduction to Data Mining
Chapter 3. Beginning with Weka and R Language
Chapter 4. Data Preprocessing
Chapter 5. Classification
Chapter 6. Implementing Classification in Weka and R
Chapter 7. Cluster Analysis
Chapter 8. Implementing Clustering with Weka and R
Chapter 9. Association Mining
Chapter 10. Implementing Association Mining with Weka and R
Chapter 11. Web Mining and Search Engines
Chapter 12. Data Warehouse
Chapter 13. Data Warehouse Schema
Chapter 14. Online Analytical Processing
Chapter 15. Big Data and NoSQL

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Data Mining and Data Warehousing: Principles and Practical Techniques
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