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Data mining : Concepts and techniques

By: Contributor(s): Material type: TextLanguage: English Publication details: Cambridge : Morgan Kaufmann is an imprint of Elsevier, 2023.Edition: 4th edDescription: xxix, 752 p. : ill. ; 24 cmISBN:
  • 9780128117606
Subject(s): Other classification:
  • D65,8(B),27 P1;R3
Summary: Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection.
Item type: Textual
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Textual Central Science Library Central Science Library D65,8(B),27 P1;R3 (Browse shelf(Opens below)) Available SL1655936

Includes bibliographical references and index.

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets.

After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection.

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