Pang-Ning Tan

Vipin Kumar

Michael Steinbach

Anuj Karpatne

Introduction to Data Mining, Second Edition, is intended for use in the Data Mining course. It is also suitable for individuals seeking an introduction to data mining. The text assumes only a modest statistics or mathematics background, and no database knowledge is needed. Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. Teaching and Learning Experience This program will provide a better teaching and learning experience-for you and your students. It will help: Present Fundamental Concepts and Algorithms: Written for the beginner, this text provides both theoretical and practical coverage of all data mining topics. Support Learning: Instructor resources include solutions for exercises and a complete set of lecture slides.

Introduction to Data Mining

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

James Bailey

Sanjay Chawla

Chin Kuan Ho

The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June 1, 2012, Proceedings, Part II

Advances in Knowledge Discovery and Data Mining, Part II

16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June1, 2012, Proceedings

Advances in Knowledge Discovery and Data Mining, Part I

Pang-Ning Tan

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