A Robust Boosting Algorithm for Chemical Modeling

Ville      A. Satopaa; Richard      D. De Veaux

doi:10.2174/157341112800392599

Abstract

Bagging and boosting have become increasingly important ensemble methods for combining models in the data mining and machine learning literature. We review the basic ideas of these methods, propose a new robust boosting algorithm based on a non-convex loss function and compare the performance of these methods to both simulated and real data sets with and without contamination.

Keywords: Bagging, Boosting, Data Mining, Machine Learning, Robust

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Current Analytical Chemistry

Title:A Robust Boosting Algorithm for Chemical Modeling

Volume: 8 Issue: 2

Author(s): Ville A. Satopaa and Richard D. De Veaux

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Keywords: Bagging, Boosting, Data Mining, Machine Learning, Robust

Abstract: Bagging and boosting have become increasingly important ensemble methods for combining models in the data mining and machine learning literature. We review the basic ideas of these methods, propose a new robust boosting algorithm based on a non-convex loss function and compare the performance of these methods to both simulated and real data sets with and without contamination.

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A. Satopaa Ville and D. De Veaux Richard, A Robust Boosting Algorithm for Chemical Modeling, Current Analytical Chemistry 2012; 8 (2) . https://dx.doi.org/10.2174/157341112800392599