1st Edition
Pattern Recognition Algorithms for Data Mining
280 Pages
by
Chapman & Hall
274 Pages
54 B/W Illustrations
by
Chapman & Hall
280 Pages
by
Chapman & Hall
Also available as eBook on:
Pattern Recognition Algorithms for Data Mining addresses different 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. This volume presents various theories, methodologies, and algorithms, using both classical... Read more
Introduction. Multiscale data condensation. Unsupervised feature selection. Active learning using support vector machine. Rough-fuzzy case generation. Rough-fuzzy clustering. Rough self-organizing map. Classification, rule generation and evaluation using modular rough-fuzzy MLP. Appendices.
Biography
Pal, Sankar K.; Mitra, Pabitra
