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Introduction

  • Gareth James
  • Daniela Witten
  • Trevor Hastie
  • Robert Tibshirani
Chapter
Part of the Springer Texts in Statistics book series (STS, volume 103)

Abstract

Statistical learning refers to a vast set of tools for understanding data. These tools can be classified as supervised or unsupervised. Broadly speaking, supervised statistical learning involves building a statistical model for predicting, or estimating, an output based on one or more inputs.

Keywords

Linear Discriminant Analysis Statistical Learning Gene Expression Measurement Wage Data Stock Market Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Gareth James
    • 1
  • Daniela Witten
    • 2
  • Trevor Hastie
    • 3
  • Robert Tibshirani
    • 3
  1. 1.Department of Information and Operations ManagementUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Department of BiostatisticsUniversity of WashingtonSeattleUSA
  3. 3.Department of StatisticsStanford UniversityStanfordUSA

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