119 citations · 417 across the 43 of their papers we have counts for
4 papers · 2 filters
fmeffects: An R Package for Forward Marginal Effects
Holger Löwe, Christian A. Scholbeck, Christian Heumann +2
Forward marginal effects have recently been introduced as a versatile and effective model-agnostic interpretation method particularly suited for non-linear and non-parametric predi…
Probabilistic Self-supervised Learning via Scoring Rules Minimization
Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer +4
In this paper, we propose a novel probabilistic self-supervised learning via Scoring Rule Minimization (ProSMIN), which leverages the power of probabilistic models to enhance repre…
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML
Lennart Purucker, Lennart Schneider, Marie Anastacio +3
Automated machine learning (AutoML) systems commonly ensemble models post hoc to improve predictive performance, typically via greedy ensemble selection (GES). However, we believe…
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models
Lennart Schneider, Bernd Bischl, Janek Thomas
We present a model-agnostic framework for jointly optimizing the predictive performance and interpretability of supervised machine learning models for tabular data. Interpretabilit…