144 citations · 392 across the 15 of their papers we have counts for
4 papers · 1 filter
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition
F. O. de Franca, M. Virgolin, M. Kommenda +21
Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main attraction of this approach is that it returns an interpretable model tha…
PMLB v1.0: An open source dataset collection for benchmarking machine learning methods
Joseph D. Romano, Trang T. Le, William La Cava +7
Motivation: Novel machine learning and statistical modeling studies rely on standardized comparisons to existing methods using well-studied benchmark datasets. Few tools exist that…
Evaluating recommender systems for AI-driven biomedical informatics
William La Cava, Heather Williams, Weixuan Fu +3
Motivation: Many researchers with domain expertise are unable to easily apply machine learning to their bioinformatics data due to a lack of machine learning and/or coding expertis…
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison
Randal S. Olson, William La Cava, Patryk Orzechowski +2
The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous p…