4 papers
Analyzing the Temporal Factors for Anxiety and Depression Symptoms with the Rashomon Perspective
Mustafa Cavus, PrzemysÅaw Biecek, Julian Tejada +2
This paper introduces a new modeling perspective in the public mental health domain to provide a robust interpretation of the relations between anxiety and depression, and the demo…
Beyond the Single-Best Model: Rashomon Partial Dependence Profile for Trustworthy Explanations in AutoML
Mustafa Cavus, Jan N. van Rijn, PrzemysÅaw Biecek
Automated machine learning systems efficiently streamline model selection but often focus on a single best-performing model, overlooking explanation uncertainty, an essential conce…
The Role of Hyperparameters in Predictive Multiplicity
Mustafa Cavus, Katarzyna Woźnica, PrzemysÅaw Biecek
This paper investigates the critical role of hyperparameters in predictive multiplicity, where different machine learning models trained on the same dataset yield divergent predict…
Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric Perspective
Mustafa Cavus, Przemyslaw Biecek
The Rashomon effect presents a significant challenge in model selection. It occurs when multiple models achieve similar performance on a dataset but produce different predictions,…