Maulik / Bandyopadhyay / Mukhopadhyay Multiobjective Genetic Algorithms for Clustering

Applications in Data Mining and Bioinformatics
1. Auflage 2011
ISBN: 978-3-642-16615-0
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 281 Seiten, eBook

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries.

The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

Zielgruppe

Graduate

Autoren/Hrsg.

Maulik, Ujjwal

Bandyopadhyay, Sanghamitra

Mukhopadhyay, Anirban

Inhaltsverzeichnis

Introduction.- Genetic Algorithms and Multiobjective Optimization.- Data Mining Fundamentals.- Computational Biology and Bioinformatics.- Multiobjective Genetic-Algorithm-Based Fuzzy Clustering.- Combining Pareto-Optimal Clusters Using Supervised Learning.- Two-Stage Fuzzy Clustering.- Clustering Categorical Data in a Multiobjective Framework.- Unsupervised Cancer Classification and Gene Marker Identification.- Multiobjective Biclustering in Microarray Gene Expression Data.- References.- Index.