An introduction to statistical learning : with applications in R / Gareth James... [et al.].
Material type:
Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
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EWU Library E-book | Non-fiction | 519.5 INT 2017 (Browse shelf(Opens below)) | Not for loan | ||||
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EWU Library Reserve Section | Non-fiction | 519.5 INT 2017 (Browse shelf(Opens below)) | C-1 | Not For Loan | 29852 | ||
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EWU Library Circulation Section | Non-fiction | 519.5 INT 2017 (Browse shelf(Opens below)) | C-2 | Available | 29853 | ||
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EWU Library Circulation Section | Non-fiction | 519.5 INT 2017 (Browse shelf(Opens below)) | C-3 | Available | 29854 |
Includes index.
TOC Introduction.- Statistical Learning.- Linear Regression.- Classification.- Resampling Methods.- Linear Model Selection and Regularization.- Moving Beyond Linearity.- Tree-Based Methods.- Support Vector Machines.- Unsupervised Learning.- Index.
This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.
CSE CSE
Sagar Shahanawaz
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