Boosting Trees for Cost-Sensitive Classifications
نویسندگان
چکیده
This paper explores two boosting techniques for cost-sensitive tree classiications in the situation where misclassiication costs change very often. Ideally, one would like to have only one induction, and use the induced model for diierent misclassiication 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 diierent aspects under this situation.
منابع مشابه
Boosting Trees for Cost-Sensitive Classi cations
This paper explores two boosting techniques for cost-sensitive tree classi cations in the situation where misclassi cation costs change very often. Ideally, one would like to have only one induction, and use the induced model for di erent misclassi cation costs. Thus, it demands robustness of the induced model against cost changes. Combining multiple trees gives robust predictions against this ...
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