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OverviewWritten 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. Full Product DetailsAuthor: Parteek BhatiaPublisher: Cambridge University Press Imprint: Cambridge University Press Dimensions: Width: 18.30cm , Height: 2.00cm , Length: 24.10cm Weight: 0.660kg ISBN: 9781108727747ISBN 10: 1108727743 Pages: 506 Publication Date: 27 June 2019 Audience: College/higher education , Tertiary & Higher Education Format: Paperback Publisher's Status: Active Availability: Temporarily unavailable  The supplier advises that this item is temporarily unavailable. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out to you. Table of ContentsPreface; Acknowledgement; Dedication; 1. Beginning with machine learning; 2. Introduction to data mining; 3. Beginning with Weka and R language; 4. Data pre-processing; 5. Classification; 6. Implementing classification in Weka and R; 7. Cluster analysis; 8. Implementing clustering with Weka and R; 9. Association mining; 10. Implementing association mining with Weka and R; 11. Web mining and search engine; 12. Operational data store and data warehouse; 13. Data warehouse schema; 14. Online analytical processing; 15. Big data and NoSQL; Reference; Index.ReviewsAuthor InformationParteek Bhatia is an associate professor in the department of computer science and engineering at Thapar Institute of Engineering and Technology, Patiala. He has more than twenty years of teaching experience and has published papers in journals. His current research includes natural language processing, machine learning and human computer interface. He has taught courses including data mining and data warehousing, big data analysis and database management system at undergraduate and graduate levels. Tab Content 6Author Website:Countries AvailableAll regions |
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