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Data Mining: Concepts and Techniques 4th edition


Data Mining: Concepts and Techniques 4th edition

Paperback by Han, Jiawei (Professor, Department of Computer ScienceUniversity of Illinois, Urbana Champaign, USA); Pei, Jian (Simon Fraser University, Burnaby, Canada); Tong, Hanghang (Associate Professor, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA)

Data Mining: Concepts and Techniques

£68.95

ISBN:
9780128117606
Publication Date:
26 Oct 2022
Edition/language:
4th edition / English
Publisher:
Elsevier Science & Technology
Imprint:
Morgan Kaufmann Publishers In
Pages:
752 pages
Format:
Paperback
For delivery:
Estimated despatch 23 May 2024
Data Mining: Concepts and Techniques

Description

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. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining.

Contents

1. Introduction 2. Data, measurements, and data processing 3. Data warehousing and online analytical processing 4. Pattern mining: basic concepts and methods 5. Pattern mining: advanced methods 6. Classification: basic concepts and methods 7. Classification: advanced methods 8. Cluster analysis: basic concepts and methods 9. Cluster analysis: advanced methods 10. Deep learning 11. Outlier Detection 12. Data mining trends and research frontiers Appendix: Mathematical background

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