Pattern Recognition Algorithms for Data Mining

Sankar K. Pal

ISBN 10: 0367394243 / ISBN 13: 9780367394240

Published by Chapman And Hall/CRC, 2019

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Seller Inventory # 9780367394240

Bibliographic Details

• Title: Pattern Recognition Algorithms for Data Mining
• Publisher: Chapman And Hall/CRC
• Publication Date: 2019
• Language: English
• ISBN 10: 0367394243
• ISBN 13: 9780367394240
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 234W x 156H x 15D millimeters 234 millimeters width by 156 millimeters height by 15 millimeters depth
• Weight: 424 grams

About this title

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.

About the Author

Pal, Sankar K.; Mitra, Pabitra