An Introduction To Statistical Learning With Applications
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Springer-Verlag GmbH
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An Introduction to Statistical Learning: with Applications in R Springer Texts in Statistics
Books Subjects Computing Internet Computer Science AI Machine Learning Books Subjects Computing Internet Software Graphics Business Home Office Books Subjects Science Nature Maths Mathematics Education Higher Education Books Subjects Science Nature Maths Mathematics Probability Statistics Books Subjects Scientific Technical Medical Mathematics Applied Mathematics Statistics Probability
Product Type: ABIS BOOK
Brand: Springer
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Springer
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
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This book presents some of the most important modeling and prediction techniques, along with relevant applications
Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented.
Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform
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A Solution Manual and Notes for: An Introduction to Statistical Learning: with Applications in R: Machine Learning (English Edition)
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