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Neural Computation, Vol 11, Issue 2 499-520, Copyright © 1999 by The MIT Press

LETTERS

Boosting regression estimators

R Avnimelech and N Intrator
Department of Computer Science, Tel-Aviv University, Ramat-Aviv, 69978, Israel.

There is interest in extending the boosting algorithm (Schapire, 1990) to fit a wide range of regression problems. The threshold-based boosting algorithm for regression used an analogy between classification errors and big errors in regression. We focus on the practical aspects of this algorithm and compare it to other attempts to extend boosting to regression. The practical capabilities of this model are demonstrated on the laser data from the Santa Fe times-series competition and the Mackey-Glass time series, where the results surpass those of standard ensemble average.


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D. L. Shrestha and D. P. Solomatine
Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression
Neural Comput., July 1, 2006; 18(7): 1678 - 1710.
[Abstract] [Full Text] [PDF]


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