Trevor Hastie & Robert Tibshirani: The Elements of Statistical Learning (ebook/PC-PDF)
2009, Sciences, Math, Probability Theory, Statistics, ISBN:
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Robert Tibshirani, author of The Elements of Statistical Learning: Data Mining, Inference, and…, on LibraryThing
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics) by Trevor Hastie; Robert Tibshirani ...
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Statistical Analysis of Gene Expression Microarray Data - Google Books
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Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer...
Boosting: Foundations and Algorithms - Robert E. Schapire, Yoav...
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An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and...
Handbook of Big Data - Google Books
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Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in...
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Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie ...
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Robert Tibshirani. A Wikipedia article about this author is available. [Info] Tibshirani, Robert: The Elements of Statistical Learning: Data Mining, Inference, and ...
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This proceedings volume provides a snapshot of the latest issues encountered in technical convergence and convergences of security technology. It explores how...
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Trevor Hastie and Robert Tibshirani are professors of statistics at Stanford University, and are co-authors of the successful textbook Elements of ...
Boosting: Foundations and Algorithms
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[217] Robert Tibshirani. Bias, variance and prediction error for classification rules. Technical report. Department of Statistics, University of Toronto, November ...
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Richard Lockhart, Jonathan Taylor, Ryan J. Tibshirani, and Robert Tibshirani. A significance test for the lasso. The Annals of Statistics, 42(2):413–468,
Proceedings - Google Books
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R package version Jerome Friedman, Trevor Hastie, and Robert Tibshirani. Regularization paths for generalized linear models via coordinate descent.
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Robert Tibshirani, Regression Shrinkage and Selection via the Lasso, J.R. Statistics, 1996, pp.(267 – 288) 12. Seyoung Kim, Kyung-Ah Sohn, Eric P. Xing.
The Science of Bradley Efron : Selected Papers | Carl N Morris,...
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New York: Springer, First Edition; First Printing. Hardcover. Near Fine with no dust jacket. Item #9599 ISBN: Slight wear. Crisp oversize...
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The Lasso and Generalizations Trevor Hastie, Robert Tibshirani, Martin Wainwright ... Stanford University Trevor Hastie and Robert Tibshirani University of ...
The Elements of Statistical Learning: Data Mining, ...
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Trevor Hastie Robert Tibshirani Department of Statistics, and Department Department of Health Research & Policy, of Health Research & Policy and Department ...
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Procedures that utilize both gene expression data and clinical data to identify subtypes of cancer can provide more accurate prognoses.
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