Pattern Recognition Algorithms for Data Mining: Scalability, Knowledge Discovery and Soft Granular Computing

by Pabitra Mitra

Pattern Recognition Algorithms for Data Mining addresses 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.

351 pages, Kindle Edition

First published April 16, 2007