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.

chapter Chapter 1|28 pages


chapter Chapter 2|30 pages

Multiscale Data Condensation

chapter Chapter 3|24 pages

Unsupervised Feature Selection

chapter Chapter 4|20 pages

Active Learning Using Support Vector Machine

chapter Chapter 5|20 pages

Rough-fuzzy Case Generation

chapter Chapter 6|26 pages

Rough-fuzzy Clustering

chapter Chapter 7|16 pages

Rough Self-Organizing Map