145 citations · 564 across the 20 of their papers we have counts for
5 papers · 1 filter
Relief-Based Feature Selection: Introduction and Review
Ryan J. Urbanowicz, Melissa Meeker, William LaCava +2
Feature selection plays a critical role in biomedical data mining, driven by increasing feature dimensionality in target problems and growing interest in advanced but computational…
A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selection
William La Cava, Thomas Helmuth, Lee Spector +1
Lexicase selection is a parent selection method that considers training cases individually, rather than in aggregate, when performing parent selection. Whereas previous work has de…
Data-driven Advice for Applying Machine Learning to Bioinformatics Problems
Randal S. Olson, William La Cava, Zairah Mustahsan +2
As the bioinformatics field grows, it must keep pace not only with new data but with new algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used ma…
Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods
William La Cava, Jason H. Moore
Recently we proposed a general, ensemble-based feature engineering wrapper (FEW) that was paired with a number of machine learning methods to solve regression problems. Here, we ad…
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…