Analytic continued fractions for regression: a memetic algorithm approach

Title: Analytic continued fractions for regression: a memetic algorithm approach
Creator: Moscato, Pablo; Sun, Haoyuan; Haque, Mohammad Nazmul
Relation: ARC.DP200102364 http://purl.org/au-research/grants/arc/DP200102364
Relation: Expert Systems with Applications Vol. 179, Issue October, 2021, no. 115018
Publisher Link: http://dx.doi.org/10.1016/j.eswa.2021.115018
Publisher: Elsevier
Resource Type: journal article
Date: 2021
Description: We present an approach for regression problems that employs analytic continued fractions as a novel representation. Comparative computational results using a memetic algorithm are reported in this work. Our experiments included fifteen other different machine learning approaches including five genetic programming methods for symbolic regression and ten machine learning methods. The comparison on training and test generalization was performed using 94 datasets of the Penn State Machine Learning Benchmark. The statistical tests showed that the generalization results using analytic continued fractions provide a powerful and interesting new alternative in the quest for compact and interpretable mathematical models for artificial intelligence.
Subject: symbolic regression; memetic algorithm; analytic continued fractions
Identifier: http://hdl.handle.net/1959.13/1461662
Identifier: uon:46269
Identifier: ISSN:0957-4174
Language: eng
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