Pattern Recognition Algorithms for Data Mining
This valuable text 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. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. The authors proceed to analyze the tasks of multi-scale data condensation and dimensionality reduction. Then they explore the problem of learning with support vector machine (SVM), and conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.
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Pattern Recognition Algorithms for Data Mining
This valuable text 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. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. The authors proceed to analyze the tasks of multi-scale data condensation and dimensionality reduction. Then they explore the problem of learning with support vector machine (SVM), and conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.
82.99 In Stock
Pattern Recognition Algorithms for Data Mining

Pattern Recognition Algorithms for Data Mining

Pattern Recognition Algorithms for Data Mining

Pattern Recognition Algorithms for Data Mining

eBook

$82.99 

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Overview

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

Product Details

ISBN-13: 9781135436391
Publisher: CRC Press
Publication date: 05/27/2004
Series: Chapman & Hall/CRC Computer Science & Data Analysis
Sold by: Barnes & Noble
Format: eBook
Pages: 280
File size: 5 MB

About the Author

Pal, Sankar K.; Mitra, Pabitra

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.
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