87 citations
- The University of Texas Rio Grande ValleyUS3 papers
- University of WarsawPL3 papers
- Warsaw University of TechnologyPL3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Instituto de Astrofísica de AndalucíaES2 papers
- Istanbul UniversityTR2 papers
- Laboratório Interinstitucional de e-AstronomiaBR2 papers
- Osservatorio Astronomico di PadovaIT2 papers
- Société Géologique de FranceFR2 papers
- Türkiye Bilimsel ve Teknolojik Araştırma KurumuTR2 papers
- Türksat (Turkey)TR2 papers
- University of Central FloridaUS2 papers
8 papers · 1 filter
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,…
A Hybrid Immersed-Boundary/Front-Tracking Method for Interface-Resolved Simulation of Droplet Evaporation
Faraz Salimnezhad, Hasret Turkeri, Iskender Gokalp +1
A hybrid sharp-interface immersed-boundary/front-tracking (IB/FT) method is developed for interface-resolved simulation of evaporating droplets in incompressible multiphase flows.…
From scale-free to Anderson localization: a size-dependent transition
Burcu Yılmaz, Cem Yuce, Ceyhun Bulutay
Scale-free localization in non-Hermitian systems is a distinctive type of localization where the localization length of certain eigenstates, known as scale-free localized (SFL) sta…
An effect analysis of the balancing techniques on the counterfactual explanations of student success prediction models
Mustafa Cavus, Jakub Kuzilek
In the past decade, we have experienced a massive boom in the usage of digital solutions in higher education. Due to this boom, large amounts of data have enabled advanced data ana…
Explainable bank failure prediction models: Counterfactual explanations to reduce the failure risk
Seyma Gunonu, Gizem Altun, Mustafa Cavus
The accuracy and understandability of bank failure prediction models are crucial. While interpretable models like logistic regression are favored for their explainability, complex…
An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced Classification
Mustafa Cavus, Przemysław Biecek
Predictive models may generate biased predictions when classifying imbalanced datasets. This happens when the model favors the majority class, leading to low performance in accurat…