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The Elements of Statistical Learning

Trevor Hastie, Robert Tibshirani, Jerome Friedman · 2009

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About the book

Describes important statistical ideas in machine learning, data mining, and bioinformatics. Covers a broad range, from supervised learning (prediction), to unsupervised learning, including classification trees, neural networks, and support vector machines.

Book details

Year
2009
Language
English
Series
Springer Series in Statistics
Publisher
Springer-Verlag New York
Editions
5
Pages
745
ISBN
9780387848570

Data source: Wikidata

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