Rough-fuzzy pattern recognition : applications in bioinformatics and medical imaging / Pradipta Maji, Sankar K. Pal.

By:

Maji, Pradipta, 1976-

Contributor(s):

Material type: Text

TextSeries: Wiley series in bioinformatics: computational techniques and engineering ; 3Publisher: Hoboken, New Jersey : John Wiley & Sons, c2012Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2012]Description: 1 PDF (xxi, 289 pages) : illustrationsContent type:

text

Media type:

electronic

Carrier type:

online resource

ISBN:

9781118119723

Subject(s):

Genre/Form:

Electronic books.

Additional physical formats: Print version:: No titleDDC classification:

610.285

Online resources:

Abstract with links to resource

Also available in print.

Contents:

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<p>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.

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Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing<p>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.