Data Mining and Data Warehousing: Principles and Practical Techniques

Book Description

Written in lucid language, this valuable textbook brings together fundamental concepts of 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 , engineering and 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 are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including analytics, relational data models and are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.

Book Details

  • Title: Data Mining and Data Warehousing: Principles and Practical Techniques
  • Author:
  • Length: 600 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2019-05-31
  • ISBN-10: 1108727743
  • ISBN-13: 9781108727747