arXiv stat.ML
· Papers
Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling
arXiv:2502.15131v5 Announce Type: replace-cross Abstract: We study the fundamental problem of calibrating a linear binary classifier of the form $sigma(hat{w}^top x)$, where the feature vector $x$ is Gaussian, $sigma$ is a link function, and $hat{w}$ is an estimator of the true linear weight $w^star$. By interpol