9780470170816 - classification analysis of dna microarrays (wiley series in bioinformatics) de peterson, leif e. (25 resultados)
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hardcover. Condición: Sehr gut. 736 Seiten; 9780470170816.2 Gewicht in Gramm: 2.
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Condición: New. pp. 736.
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Hardcover. Condición: new. Hardcover. Wiley Series in Bioinformatics: Computational Techniques and Engineering Yi Pan and Albert Y. Zomaya, Series Editors Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in D…NA microarray studies Proliferating 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 studiesServes as a historical repository of general use supervised classification methods as well as newer contemporary methodsBrings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the bookDescribes implementation methods that help shorten discovery times Classification Analysis of DNA Microarrays is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Mixed Media Product. Condición: New. Wiley Series in Bioinformatics: Computational Techniques and Engineering Yi Pan and Albert Y. Zomaya, Series Editors Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in DN…A microarray studies Proliferating 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 studiesServes as a historical repository of general use supervised classification methods as well as newer contemporary methodsBrings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the bookDescribes implementation methods that help shorten discovery times Classification Analysis of DNA Microarrays is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields.
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Condición: 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 litera…ture. 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. . . . .
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Hardcover. Condición: new. Hardcover. Wiley Series in Bioinformatics: Computational Techniques and Engineering Yi Pan and Albert Y. Zomaya, Series Editors Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in D…NA microarray studies Proliferating 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 studiesServes as a historical repository of general use supervised classification methods as well as newer contemporary methodsBrings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the bookDescribes implementation methods that help shorten discovery times Classification Analysis of DNA Microarrays is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Condición: 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.
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Condición: 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 litera…ture. 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.
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Hardcover. Condición: Brand New. 1st edition. 736 pages. 9.75x6.50x1.75 inches. In Stock.
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Mixed Media Product. Condición: New. Wiley Series in Bioinformatics: Computational Techniques and Engineering Yi Pan and Albert Y. Zomaya, Series Editors Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in DN…A microarray studies Proliferating 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 studiesServes as a historical repository of general use supervised classification methods as well as newer contemporary methodsBrings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the bookDescribes implementation methods that help shorten discovery times Classification Analysis of DNA Microarrays is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields.
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Hardcover. Condición: new. Hardcover. Wiley Series in Bioinformatics: Computational Techniques and Engineering Yi Pan and Albert Y. Zomaya, Series Editors Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in D…NA microarray studies Proliferating 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 studiesServes as a historical repository of general use supervised classification methods as well as newer contemporary methodsBrings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the bookDescribes implementation methods that help shorten discovery times Classification Analysis of DNA Microarrays is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Taschenbuch. Condición: 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 infor…mation 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.
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Hardcover. Condición: Brand New. 1st edition. 736 pages. 9.75x6.50x1.75 inches. In Stock. This item is printed on demand.
