Pattern Recognition Algorithms for Data Mining - Scalability, Knowledge Discovery and Soft Granular Computing (Hardcover, New)

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.

General

Imprint:	Chapman & Hall/CRC
Country of origin:	United States
Series:	Chapman & Hall/CRC Computer Science & Data Analysis
Release date:	May 2004
First published:	2004
Authors:	Sankar K. Pal • Pabitra Mitra
Dimensions:	234 x 156 x 22mm (L x W x T)
Format:	Hardcover
Pages:	274
Edition:	New
ISBN-13:	978-1-58488-457-6
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	1-58488-457-6
Barcode:	9781584884576

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