32 citations · 87 across the 13 of their papers we have counts for
4 papers · 1 filter
Automatically Balancing Model Accuracy and Complexity using Solution and Fitness Evolution (SAFE)
Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz
When seeking a predictive model in biomedical data, one often has more than a single objective in mind, e.g., attaining both high accuracy and low complexity (to promote interpreta…
Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems
Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz
We have recently presented SAFE -- Solution And Fitness Evolution -- a commensalistic coevolutionary algorithm that maintains two coevolving populations: a population of candidate…
Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions
Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz
We recently highlighted a fundamental problem recognized to confound algorithmic optimization, namely, \textit{conflating} the objective with the objective function. Even when the…
STREAMLINE: A Simple, Transparent, End-To-End Automated Machine Learning Pipeline Facilitating Data Analysis and Algorithm Comparison
Ryan J. Urbanowicz, Robert Zhang, Yuhan Cui +1
Machine learning (ML) offers powerful methods for detecting and modeling associations often in data with large feature spaces and complex associations. Many useful tools/packages (…