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Pattern Recognition Algorithms for Data Mining: Scalability, Knowledge Discovery and Soft Granular Computing (Chapman & Hall/CRC Computer Science & Data Analysis) by Sankar K Pal; Pabitra Mitra, PhD is a nonfiction available to read on EtoBox.

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

<p>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.</p> <p>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.</p>

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

Author

Sankar K Pal; Pabitra Mitra, PhD

Publisher

Chapman and Hall/CRC

Published

2004

Language

EN

ISBN

9782004043535

Category

nonfiction

Subjects

Computer Science, Mathematics, Science