Leo Breiman

Random Forests

The Little Bootstrap and other Methods for Dimensionality Selection in Regression: X-Fixed Prediction Error

Abstract When a regression problem contains many predictor variables, it is rarely wise to try to fit the data by means of a least squares regression on all of the predictor var...

Classification and Regression Trees.

Bagging predictors

Prediction Games and Arcing Algorithms

The theory behind the success of adaptive reweighting and combining algorithms (arcing) such as Adaboost (Freund & Schapire, 1996a, 1997) and others in reducing generalizati...

Heuristics of instability and stabilization in model selection

In model selection, usually a "best" predictor is chosen from a collection ${\\hat{\\mu}(\\cdot, s)}$ of predictors where $\\hat{\\mu}(\\cdot, s)$ is the minimum least-squares p...

Better Subset Regression Using the Nonnegative Garrote

A new method, called the nonnegative (nn) garrote, is proposed for doing subset regression. It both shrinks and zeroes coefficients. In tests on real and simulated data, it prod...