Multiobjective Genetic Algorithms for Clustering: Applications in Data Mining and Bioinformatics
Autor Ujjwal Maulik, Sanghamitra Bandyopadhyay, Anirban Mukhopadhyayen Limba Engleză Paperback – 23 noi 2014
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.
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Springer Berlin, Heidelberg – 23 noi 2014 | 323.10 lei 6-8 săpt. | |
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Springer Berlin, Heidelberg – 2 sep 2011 | 327.41 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783642439636
ISBN-10: 3642439632
Pagini: 300
Ilustrații: XVI, 281 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.42 kg
Ediția:2011
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642439632
Pagini: 300
Ilustrații: XVI, 281 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.42 kg
Ediția:2011
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
GraduateCuprins
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.
Textul de pe ultima copertă
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.
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.
Caracteristici
Book introduces many original ideas Significant contribution to the field Authors detail collaborations in biological and data mining applications