Year: 2022
Type: conference-paper
Abstract: We present three evolutionary symbolic regression-based classification algorithms for binary and multinomial datasets: GPLearnClf CartesianClf and ClaSyCo. Tested over 162 datasets and compared to three state-of-the-art machine learning algorithms---XGBoost, LightGBM, and a deep neural network---we find our algorithms to be competitive. Further, we demonstrate how to find the best method for one's dataset automatically, through the use of a state-of-the-art hyperparameter optimizer.
Author: Moshe Sipper
Institution: Ben-Gurion University of the Negev
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4283714743