The authors propose an inverse conformal prediction method for estimating misclassification risk in multi-class classifiers and show empirically that it is competitive with calibration techniques while being conservative.
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An In-Depth Examination of Risk Assessment in Multi-Class Classification Algorithms
The authors propose an inverse conformal prediction method for estimating misclassification risk in multi-class classifiers and show empirically that it is competitive with calibration techniques while being conservative.