Frontmatter -- Introduction to Pattern Recognition and Data Mining -- Rough-Fuzzy Hybridization and Granular Computing -- Rough-Fuzzy Clustering: Generalized A-Means Algorithm -- Rough-Fuzzy Granulation and Pattern Classification -- Fuzzy-Rough Feature Selection using -Information Measures -- Rough Fuzzy -Medoids and Amino Acid Sequence Analysis -- Clustering Functionally Similar Genes from Microarray Data -- Selection of Discriminative Genes from Microarray Data -- Segmentation of Brain Magnetic Resonance Images -- Index
Summary
Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems development, making it easier to master such tasks as classification, clustering, and feature selection
