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"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.
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Advances in Knowledge Discovery and Data Mining, Part I - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June1, 2012, Proceedings, Part I (Paperback)
Pang-Ning Tan, Sanjay Chawla, Chin Kuan Ho, James Bailey
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R1,667
Discovery Miles 16 670
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Ships in 10 - 15 working days
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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.
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Advances in Knowledge Discovery and Data Mining, Part II - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June 1, 2012, Proceedings, Part II (Paperback, 2012 ed.)
Pang-Ning Tan, Sanjay Chawla, Chin Kuan Ho, James Bailey
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R1,611
Discovery Miles 16 110
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Ships in 10 - 15 working days
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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.
Introducing the fundamental concepts and algorithms of data mining
Introduction to Data Mining, 2nd Edition, gives a comprehensive
overview of the background and general themes of data mining and is
designed to be useful to students, instructors, researchers, and
professionals. Presented in a clear and accessible way, the book
outlines fundamental concepts and algorithms for each topic, thus
providing the reader with the necessary background for the
application of data mining to real problems. The text helps readers
understand the nuances of the subject, and includes important
sections on classification, association analysis, and cluster
analysis. This edition improves on the first iteration of the book,
published over a decade ago, by addressing the significant changes
in the industry as a result of advanced technology and data growth.
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