principles and practical techniques Bhatia, Parteek creator author. text bibliography enk New York Cambridge University Press c2019 [reprinted 2022] 2019 monographic eng

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xxxiv, 477 pages : illustrations (some color) ; 24 cm "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"-- Parteek Bhatia. Includes bibliographical references and index. Data mining Textbooks Data warehousing Textbooks 006.312 9781108727747 2019013358 LBSOR/DLC 241127 20241127104130.0 20922191 eng