9781493938322 - modern multivariate statistical techniques: regression, classification, and manifold learning (springer texts in statistics) de izenman, alan j. (11 resultados)
Idioma: Inglés
Editorial: Springer 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: HPB-Red, Dallas, TX, Estados Unidos de AmericaHPB-Red
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Idioma: Inglés
Editorial: Springer 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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Editorial: Humana 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Taschenbuch. Condición: Neu. Modern Multivariate Statistical Techniques | Regression, Classification, and Manifold Learning | Alan J. Izenman | Taschenbuch | Springer Texts in Statistics | xxv | Englisch | 2016 | Humana | EAN 9781493938322 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidel…berg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Editorial: Springer 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books
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Idioma: Inglés
Editorial: Springer, Humana 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has… opened up the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion of database management systems.This book is appropriate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and probability and statistics is required. The book presents a carefully-integrated mixture of theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as examples in the book, over 200 exercises, and many color illustrations and photographs.
Idioma: Inglés
Editorial: Springer 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
Idioma: Inglés
Editorial: Springer, Humana Aug 2016 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Ge…nome Project has opened up the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion of database management systems.This book is appropriate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and probability and statistics is required. The book presents a carefully-integrated mixture of theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as examples in the book, over 200 exercises, and many color illustrations and photographs. 760 pp. Englisch.
Idioma: Inglés
Editorial: Springer New York 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: moluna, Greven, Alemaniamoluna
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Describes database management systems for maintaining and querying large databasesProvides detailed descriptions of linear and nonlinear data-mining and machine-learning techniquesIntegrates t…heory, real-data examples from many scientific d.
Idioma: Inglés
Editorial: Springer 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Idioma: Inglés
Editorial: Springer 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. PRINT ON DEMAND.
Idioma: Inglés
Editorial: Springer, Humana Aug 2016 2016
Serie: Springer Texts in Statistics, Libro 36 de 111. Libro 36 de 111 - Springer Texts in Statistics
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome… Project has opened up the field of bioinformatics.These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion of database management systems.This book is appropriate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and probability and statistics is required. The book presents a carefully-integrated mixture of theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as examples in the book, over 200 exercises, and many color illustrations and photographs.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 760 pp. Englisch.
