Data mining and data warehousing : principles and practical techniques / Parteek Bhatia.
"This 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. It brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics in...
Main Author: | |
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Language: | English |
Published: |
Cambridge, United Kingdom ; New York, NY :
Cambridge University Press,
2019.
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Subjects: | |
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Physical Description: | xxix, 477 pages ; 25 cm |
Format: | Book |
Summary: |
"This 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. It 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 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. Unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding"-- Provided by publisher. |
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Call Number: | QA76.9.D343 B435 2019 |
Bibliography Note: | Includes bibliographical references and index. |
ISBN: | 9781108727747 1108727743 |