Pattern Recognition Algorithms for Data Mining: Scalability, Knowledge Discovery and Soft Granular Computing (Chapman & Hall/CRC Computer Science & Data Analysis)

Editor

Chapman and Hall/CRC

Fecha de publicaci�n

2019

Idioma

Ingl�s

ISBN 10

0367394243

ISBN 13

9780367394240

Encuadernaci�n

Encuadernaci�n de tapa blanda

Estado

New

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Sinopsis

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.

Acerca del autor

Pal, Sankar K.; Mitra, Pabitra

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