Pattern Recognition Algorithms for Data Mining by Pabitra Mitra
(Chapman & Hall/CRC Computer Science & Data Analysis)

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Synopsis

Pattern Recognition Algorithms for Data Mining addresses pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. The authors proceed to analyze the tasks of multi-scale data condensation and dimensionality reduction. Then they explore the problem of learning with support vector machine (SVM), and conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

 

About Pabitra Mitra

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SANKAR K. PAL, PhD, is a Distinguished Scientist and founding head of the Machine Intelligence Unit at the Indian Statistical Institute, Calcutta. Professor Pal holds several PhDs and is a Fellow of the IEEE and IAPR. SIMON C. K. SHIU, PhD, is Assistant Professor in the Department of Computing at Hong Kong Polytechnic University.
 
Published April 16, 2007 by Chapman & Hall/CRC. 280 pages
Genres: Computers & Technology, Education & Reference, Professional & Technical, Science & Math, Literature & Fiction. Non-fiction

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