A cross-benchmark examination of feature-based algorithm selector generalization in single-objective numerical optimization

G Cenikj, G Petelin, T Eftimov - Swarm and Evolutionary Computation, 2024 - Elsevier
The task of selecting the best optimization algorithm for a particular problem is known as
algorithm selection (AS). This involves training a model using landscape characteristics to …

[PDF][PDF] Predicting student performance using Moodle data and machine learning with feature importance

JK Rogers, TC Mercado, R Cheng - Indonesian J. Electr. Eng …, 2025 - researchgate.net
Despite the growing technological advancement in education, poor academic performance
of students remains challenging for educational institutions worldwide. The study aimed to …

A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization

G Cenikj, A Nikolikj, G Petelin, N van Stein… - arxiv preprint arxiv …, 2024 - arxiv.org
The selection of the most appropriate algorithm to solve a given problem instance, known as
algorithm selection, is driven by the potential to capitalize on the complementary …

Generalization Ability of Feature-based Performance Prediction Models: A Statistical Analysis across Benchmarks

A Nikolikj, A Kostovska, G Cenikj, C Doerr… - arxiv preprint arxiv …, 2024 - arxiv.org
This study examines the generalization ability of algorithm performance prediction models
across various benchmark suites. Comparing the statistical similarity between the problem …