On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL

no code implementations • 13 Jul 2017 • Marco Loog, Jesse H. Krijthe, Are C. Jensen

In various approaches to learning, notably in domain adaptation, active learning, learning under covariate shift, semi-supervised learning, learning with concept drift, and the like, one often wants to compare a baseline classifier to one or more advanced (or at least different) strategies.

Active Learning Domain Adaptation +1