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An introduction to statistical learning : with applications in R /

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Bibliographic Details
Main Authors: James, Gareth (Gareth Michael) (Author), Witten, Daniela (Author), Hastie, Trevor (Author), Tibshirani, Robert (Author)
Corporate Author: EBSCOhost
Format: eBook
Language:English
Published: New York : Springer, [2013]
Edition:[Uncorrected edition].
Series:Springer texts in statistics.
Subjects:
Mathematical statistics.
Mathematical models.
Mathematical statistics > Problems, exercises, etc.
Mathematical models > Problems, exercises, etc.
R (Computer program language)
Statistics.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Introduction
  • Statistical learning
  • Linear regression
  • Classification
  • Resampling methods
  • Linear model selection and regularization
  • Moving beyond linearity
  • Tree-based methods
  • Support vector machines
  • Unsupervised learning.