The elements of statistical learning : data mining, inference, and prediction / Trevor Hastie, Robert Tibshirani, Jerome Friedman. [electronic resource]
Material type:
Computer filePublication details: New York, : Springer, 2009Edition: Second editionDescription: 1 online resource : illustrationsISBN: - 9780387848587 (E-book)
- Q 325.5 H37E 2009
| Item type | Current library | Collection | Shelving location | Call number | Status | Barcode | Course reserves | |
|---|---|---|---|---|---|---|---|---|
E-Book
|
SPU Library, Bangkok (Main Campus) | Electronic Resources | On Display | Q 325.5 H37E 2009 (Browse shelf(Opens below)) | Available | 9780387848587 |
Includes bibliographical references (p. [699]-727) and index
Introduction -- Overview of Supervised Learning -- Linear Methods for Regression -- Linear Methods for Classification -- Basis Expansions and Regularization -- Kernel Smoothing Methods -- Model Assessment and Selection -- Model Inference and Averaging -- Additive Models, Trees, and Related Methods -- Boosting and Additive Trees -- Neural Networks -- Support Vector Machines and Flexible Discriminants -- Prototype Methods and Nearest-Neighbors -- Unsupervised Learning -- Random Forests -- Ensemble Learning -- Undirected Graphical Models -- High-Dimensional Problems: p ≫ N
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