Description: Pattern Recognition Algorithms for Data Mining Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Sankar K. Pal, Pabitra Mitra Format: Hardback Publisher: Taylor & Francis Inc, United States Imprint: Chapman & Hall/CRC ISBN-13: 9781584884576, 978-1584884576 Synopsis 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.
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Book Title: Pattern Recognition Algorithms for Data Mining
Number of Pages: 280 Pages
Language: English
Publication Name: Pattern Recognition Algorithms for Data Mining
Publisher: Taylor & Francis INC International Concepts
Publication Year: 2004
Subject: Computer Science
Item Height: 234 mm
Item Weight: 522 g
Type: Textbook
Author: Pabitra Mitra, Sankar K. Pal
Series: Chapman & Hall/Crc Computer Science & Data Analysis
Item Width: 156 mm
Format: Hardcover
