arXiv:2604.20409v1 Announce Type: cross Abstract: We introduce and study the problem of calibrating conditional risk, which involves estimating the expected loss of a prediction model conditional on input features. We analyze this problem in both classification and regression settings and show that it is fundamentally equivalent to a standard regression task. For classification settings, we furthe
Calibrating conditional risk
Andrey Vasilyev, Yikai Wang, Xiaocheng Li, Guanting Chen·arXiv stat.ML··1 min read
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