ML Anthology

A Monte Carlo Analysis of Ensemble Classification

Roberto Esposito, Lorenza Saitta
ICML 2004
doi:10.1145/1015330.1015386 /icml/2004/esposito2004icml-monte/

Abstract

In this paper we extend previous results providing a theoretical analysis of a new Monte Carlo ensemble classifier. The framework allows us to characterize the conditions under which the ensemble approach can be expected to outperform the single hypothesis classifier. Moreover, we provide a closed form expression for the distribution of the true ensemble accuracy, as well as of its mean and variance. We then exploit this result in order to analyze the expected error behavior in a particularly interesting case.

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Cite

Text

Esposito and Saitta. "A Monte Carlo Analysis of Ensemble Classification." International Conference on Machine Learning, 2004. doi:10.1145/1015330.1015386

Markdown

[Esposito and Saitta. "A Monte Carlo Analysis of Ensemble Classification." International Conference on Machine Learning, 2004.](https://mlanthology.org/icml/2004/esposito2004icml-monte/) doi:10.1145/1015330.1015386

BibTeX

@inproceedings{esposito2004icml-monte,
  title     = {{A Monte Carlo Analysis of Ensemble Classification}},
  author    = {Esposito, Roberto and Saitta, Lorenza},
  booktitle = {International Conference on Machine Learning},
  year      = {2004},
  doi       = {10.1145/1015330.1015386},
  url       = {https://mlanthology.org/icml/2004/esposito2004icml-monte/}
}