Sprache: Englisch
Verlag: Wiley-IEEE Computer Society Pr, 2013
ISBN 10: 0470170816 ISBN 13: 9780470170816
Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Zustand: Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
Sprache: Englisch
Verlag: Wiley-IEEE Computer Society Pr, 2013
ISBN 10: 0470170816 ISBN 13: 9780470170816
Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Zustand: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
EUR 97,85
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In den WarenkorbUNK. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
Verlag: Wiley-IEEE Computer Society Pr, 2013
ISBN 10: 0470170816 ISBN 13: 9780470170816
Anbieter: Studibuch, Stuttgart, Deutschland
hardcover. Zustand: Sehr gut. 736 Seiten; 9780470170816.2 Gewicht in Gramm: 2.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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In den WarenkorbZustand: New. pp. 736.
EUR 117,27
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In den WarenkorbZustand: New. LEIF E. PETERSON, PhD, is Associate Professor of Public Health, Weill Cornell Medical College, Cornell University, and is with the Center for Biostatistics, The Methodist Hospital Research Institute (Houston). He is a member of the IEEE Computational Intell.
Zustand: New. The rapid uncontrolled growth of classification methods in DNA microarray studies has resulted in a body of information scattered throughout literature, numerous conference proceedings, and others. This book brings together many of the unsupervised and supervised classification methods now dispersed in the literature. Series: Wiley Series in Bioinformatics. Num Pages: 736 pages, Illustrations. BIC Classification: PSAK1. Category: (P) Professional & Vocational. Dimension: 241 x 163 x 41. Weight in Grams: 1178. . 2013. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 158,12
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 736 pages. 9.75x6.50x1.75 inches. In Stock.
Taschenbuch. Zustand: Neu. Neuware - Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in DNA microarray studiesProliferating classification methods in DNA microarray studies have resulted in a body of information scattered throughout literature, conference proceedings, and elsewhere. This book unites many of these classification methods in a single volume. In addition to traditional statistical methods, it covers newer machine-learning approaches such as fuzzy methods, artificial neural networks, evolutionary-based genetic algorithms, support vector machines, swarm intelligence involving particle swarm optimization, and more.Classification Analysis of DNA Microarrays provides highly detailed pseudo-code and rich, graphical programming features, plus ready-to-run source code. Along with primary methods that include traditional and contemporary classification, it offers supplementary tools and data preparation routines for standardization and fuzzification; dimensional reduction via crisp and fuzzy c-means, PCA, and non-linear manifold learning; and computational linguistics via text analytics and n-gram analysis, recursive feature extraction during ANN, kernel-based methods, ensemble classifier fusion.This powerful new resource:\* Provides information on the use of classification analysis for DNA microarrays used for large-scale high-throughput transcriptional studies\* Serves as a historical repository of general use supervised classification methods as well as newer contemporary methods\* Brings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the book\* Describes implementation methods that help shorten discovery timesClassification Analysis of DNA Microarrays is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields.