preprint · arXiv (Cornell University) · 2016

Bayesian Hyperparameter Optimization for Ensemble Learning

Julien-Charles Lévesque, Christian Gagné, Robert Sabourin

Cited by 35Open access

Abstract

In this paper, we bridge the gap between hyperparameter optimization and ensemble learning by performing Bayesian optimization of an ensemble with regards to its hyperparameters. Our method consists in building a fixed-size ensemble, optimizing the configuration of one classifier of the ensemble at each iteration of the hyperparameter optimization algorithm, taking into consideration the interaction with the other models when evaluating potential performances. We also consider the case where the ensemble is to be reconstructed at the end of the hyperparameter optimization phase, through a greedy selection over the pool of models generated during the optimization. We study the performance of our proposed method on three different hyperparameter spaces, showing that our approach is better than both the best single model and a greedy ensemble construction over the models produced by a standard Bayesian optimization.

Cite this paper

APA 7

Lévesque, J.-C., Gagné, C., & Sabourin, R. (2016). Bayesian Hyperparameter Optimization for Ensemble Learning. arXiv (Cornell University). https://doi.org/10.48550/arxiv.1605.06394

MLA 9

Lévesque, Julien-Charles, et al. “Bayesian Hyperparameter Optimization for Ensemble Learning.” arXiv (Cornell University), 2016, https://doi.org/10.48550/arxiv.1605.06394.

Chicago

Lévesque, Julien-Charles, Christian Gagné, and Robert Sabourin. 2016. “Bayesian Hyperparameter Optimization for Ensemble Learning.” arXiv (Cornell University). https://doi.org/10.48550/arxiv.1605.06394.

Harvard

Lévesque, J.-C., Gagné, C. and Sabourin, R. (2016) ‘Bayesian Hyperparameter Optimization for Ensemble Learning’, arXiv (Cornell University). Available at: https://doi.org/10.48550/arxiv.1605.06394.

BibTeX

@misc{levesque2016bayesian,
  title = {{Bayesian Hyperparameter Optimization for Ensemble Learning}},
  author = {Lévesque, Julien-Charles and Gagné, Christian and Sabourin, Robert},
  journal = {arXiv (Cornell University)},
  year = {2016},
  doi = {10.48550/arxiv.1605.06394}
}

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