3 papers
cs.LG2025
Recalibrating binary probabilistic classifiers
Dirk Tasche
Recalibration of binary probabilistic classifiers to a target prior probability is an important task in areas like credit risk management. However, recalibration of a classifier le…
cs.LG2024
Comments on Friedman's Method for Class Distribution Estimation
Dirk Tasche
The purpose of class distribution estimation (also known as quantification) is to determine the values of the prior class probabilities in a test dataset without class label observ…
cs.LG2023
Invariance assumptions for class distribution estimation
Dirk Tasche
We study the problem of class distribution estimation under dataset shift. On the training dataset, both features and class labels are observed while on the test dataset only the f…