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The Elements of Statistical Learning, Second Edition

Data Mining, Inference, and Prediction
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Verfasser: Suche nach diesem Verfasser Hastie, Trevor (Geistiger Schöpfer); Tibshirani, Robert (Geistiger Schöpfer); Friedman, Jerome (Geistiger Schöpfer)
Jahr: 2009
Verlag: Berlin, Springer New York
Reihe: Springer Series in Statistics
Mediengruppe: Dauerleihe
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Inhalt

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.
 
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates.

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Verfasserangabe: Trevor Hastie ; Robert Tibshirani ; Jerome Friedman
Jahr: 2009
Verlag: Berlin, Springer New York
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Systematik: Suche nach dieser Systematik MA-10
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ISBN: 9780387848570
ISSN: 0172-7397
Beschreibung: 2nd edition, XX, 744 Seiten
Reihe: Springer Series in Statistics
Schlagwörter: Bioinformatics; Algorithms; Data mining; Machine learning; Neural networks ( Computer science); Statistical methods
Beteiligte Personen: Suche nach dieser Beteiligten Person Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome
Sprache: Englisch
Originaltitel: The Elements of Statistical Learning, Second Edition
Mediengruppe: Dauerleihe