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- Trevor J. Hastie, Robert Tibshirani, Jerome H. Friedman
- Springer series in statistics
- 2009

by E.T. Jaynes CAMBRIDGE, CAMBRIDGE UNIVERSITY PRESS, 2003 727pp. $65.00 HARDBACK ISBN 0-521-59271-2 The Fundamentals of Risk Measurement by Chris Marrison BOSTON, McGRAW-HILL, 2002 415pp. $44.95â€¦ (More)

Boosting is one of the most important recent developments in classification methodology. Boosting works by sequentially applying a classification algorithm to reweighted versions of the training dataâ€¦ (More)

The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will beâ€¦ (More)

- Jerome H. Friedman, Trevor J. Hastie, Rob Tibshirani
- Journal of statistical software
- 2010

We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problemsâ€¦ (More)

- T SÃ¸rlie, Charles M. Perou, +14 authors A L BÃ¸rresen-Dale
- Proceedings of the National Academy of Sciencesâ€¦
- 2001

The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. Aâ€¦ (More)

- Jerome H. Friedman, Trevor J. Hastie, Robert Tibshirani
- Biostatistics
- 2008

We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm--theâ€¦ (More)

- Robert Tibshirani, Trevor J. Hastie, B. Narasimhan, Gilbert Chu
- Proceedings of the National Academy of Sciencesâ€¦
- 2002

We have devised an approach to cancer class prediction from gene expression profiling, based on an enhancement of the simple nearest prototype (centroid) classifier. We shrink the prototypes andâ€¦ (More)

- Jane Elith, John R. Leathwick, Trevor J. Hastie
- The Journal of animal ecology
- 2008

1. Ecologists use statistical models for both explanation and prediction, and need techniques that are flexible enough to express typical features of their data, such as nonlinearities andâ€¦ (More)

Principal component analysis (PCA) is widely used in data processing and dimensionality reduction. However, PCA suffers from the fact that each principal component is a linear combination of all theâ€¦ (More)

- Therese Sorlie, Robert Tibshirani, +13 authors David Botstein
- Proceedings of the National Academy of Sciencesâ€¦
- 2003

Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously definedâ€¦ (More)