115 citations · 140 across the 3 of their papers we have counts for
4 papers
An Introduction to Algorithmic Fairness
Hilde J. P. Weerts
In recent years, there has been an increasing awareness of both the public and scientific community that algorithmic systems can reproduce, amplify, or even introduce unfairness in…
Importance of Tuning Hyperparameters of Machine Learning Algorithms
Hilde J. P. Weerts, Andreas C. Mueller, Joaquin Vanschoren
The performance of many machine learning algorithms depends on their hyperparameter settings. The goal of this study is to determine whether it is important to tune a hyperparamete…
Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models
Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy
In many contexts, it can be useful for domain experts to understand to what extent predictions made by a machine learning model can be trusted. In particular, estimates of trustwor…
A Human-Grounded Evaluation of SHAP for Alert Processing
Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy
In the past years, many new explanation methods have been proposed to achieve interpretability of machine learning predictions. However, the utility of these methods in practical a…