Pattern Recognition Algorithms for Data Mining: 1st Edition (Paperback) book cover

Pattern Recognition Algorithms for Data Mining

1st Edition

By Sankar K. Pal, Pabitra Mitra

Chapman and Hall/CRC

280 pages

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Paperback: 9780367394240
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Description

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 approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.

Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

Table of Contents

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.

About the Authors

Pal, Sankar K.; Mitra, Pabitra

About the Series

Chapman & Hall/CRC Computer Science & Data Analysis

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Subject Categories

BISAC Subject Codes/Headings:
COM000000
COMPUTERS / General
COM012040
COMPUTERS / Programming / Games
COM021030
COMPUTERS / Database Management / Data Mining
COM051300
COMPUTERS / Programming / Algorithms