research
∙
03/29/2023
Sparse joint shift in multinomial classification
Sparse joint shift (SJS) was recently proposed as a tractable model for ...
share
research
∙
07/29/2022
Factorizable Joint Shift in Multinomial Classification
Factorizable joint shift (FJS) was recently proposed as a type of datase...
research
∙
06/06/2022
Class Prior Estimation under Covariate Shift – no Problem?
We show that in the context of classification the property of source and...
research
∙
07/17/2021
Minimising quantifier variance under prior probability shift
For the binary prevalence quantification problem under prior probability...
research
∙
05/15/2021
Calibrating sufficiently
When probabilistic classifiers are trained and calibrated, the so-called...
research
∙
05/07/2020
Proving prediction prudence
We study how to perform tests on samples of pairs of observations and pr...
research
∙
06/10/2019
Confidence intervals for class prevalences under prior probability shift
Point estimation of class prevalences in the presence of data set shift ...
research
∙
04/09/2018
A plug-in approach to maximising precision at the top and recall at the top
For information retrieval and binary classification, we show that precis...
research
∙
01/19/2017
Fisher consistency for prior probability shift
We introduce Fisher consistency in the sense of unbiasedness as a desira...
research
∙
02/28/2016
Does quantification without adjustments work?
Classification is the task of predicting the class labels of objects bas...
research
∙
06/23/2014
Exact fit of simple finite mixture models
How to forecast next year's portfolio-wide credit default rate based on ...
research
∙
12/02/2013