1 code implementation • 20 Feb 2019 • Lukas Pfannschmidt, Jonathan Jakob, Michael Biehl, Peter Tino, Barbara Hammer
The increasing occurrence of ordinal data, mainly sociodemographic, led to a renewed research interest in ordinal regression, i. e. the prediction of ordered classes.
no code implementations • 2 Mar 2019 • Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer
Most existing feature selection methods are insufficient for analytic purposes as soon as high dimensional data or redundant sensor signals are dealt with since features can be selected due to spurious effects or correlations rather than causal effects.
no code implementations • 10 Dec 2019 • Lukas Pfannschmidt, Jonathan Jakob, Fabian Hinder, Michael Biehl, Peter Tino, Barbara Hammer
In this contribution, we focus on feature selection paradigms, which enable us to uncover relevant factors of a given regularity based on a sparse model.
3 code implementations • 1 Apr 2020 • Lukas Pfannschmidt, Barbara Hammer
The problem of all-relevant feature selection is concerned with finding a relevant feature set with preserved redundancies.