4.7 Article Proceedings Paper

Conditional validity of inductive conformal predictors

期刊

MACHINE LEARNING
卷 92, 期 2-3, 页码 349-376

出版社

SPRINGER
DOI: 10.1007/s10994-013-5355-6

关键词

Inductive conformal predictors; Conditional validity; Batch mode of learning; ROC curves; Boosting; MART; Spam detection

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Conformal predictors are set predictors that are automatically valid in the sense of having coverage probability equal to or exceeding a given confidence level. Inductive conformal predictors are a computationally efficient version of conformal predictors satisfying the same property of validity. However, inductive conformal predictors have only been known to control unconditional coverage probability. This paper explores various versions of conditional validity and various ways to achieve them using inductive conformal predictors and their modifications. In particular, it discusses a convenient expression of one of the modifications in terms of ROC curves.

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