paper:boosting regression

[Harris Drucker]

FTP-host: archive.cis.ohio-state.edu
FTP-filename: /pub/neuroprose/drucker.boosting-regression.ps.Z

The following paper on regression was presented at the Fourteenth International
Conference on Machine Learning(1997), Morgan Kaufmann, publishers: 

Improving Regressors using Boosting Techniques

Harris Drucker
Monmouth University
West Long Branch, NJ 07764
drucker at monmouth.edu

Abstract

In the regression context, boosting and bagging are techniques to
build a committee of regressors that may be superior to a single
regressor.  We use regression trees as fundamental building blocks in
bagging committee machines and boosting committee machines.
Performance is analyzed on three non-linear functions and the Boston
housing database.  In all cases, boosting is at least equivalent, and
in most cases better than bagging in terms of prediction error.

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