ML Anthology

Boosting Trees for Cost-Sensitive Classifications

Kai Ming Ting, Zijian Zheng
ECML-PKDD 1998 pp. 190-195
doi:10.1007/BFB0026689 /ecmlpkdd/1998/ting1998ecml-boosting/

Abstract

This paper explores two boosting techniques for cost-sensitive tree classifications in the situation where misclassification costs change very often. Ideally, one would like to have only one induction, and use the induced model for different misclassification costs. Thus, it demands robustness of the induced model against cost changes. Combining multiple trees gives robust predictions against this change. We demonstrate that the two boosting techniques are a good solution in different aspects under this situation.

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Cite

Text

Ting and Zheng. "Boosting Trees for Cost-Sensitive Classifications." European Conference on Machine Learning, 1998. doi:10.1007/BFB0026689

Markdown

[Ting and Zheng. "Boosting Trees for Cost-Sensitive Classifications." European Conference on Machine Learning, 1998.](https://mlanthology.org/ecmlpkdd/1998/ting1998ecml-boosting/) doi:10.1007/BFB0026689

BibTeX

@inproceedings{ting1998ecml-boosting,
  title     = {{Boosting Trees for Cost-Sensitive Classifications}},
  author    = {Ting, Kai Ming and Zheng, Zijian},
  booktitle = {European Conference on Machine Learning},
  year      = {1998},
  pages     = {190-195},
  doi       = {10.1007/BFB0026689},
  url       = {https://mlanthology.org/ecmlpkdd/1998/ting1998ecml-boosting/}
}