Learning Functions and Classes Using Rules

In the current work, a novel method is presented for generating rules for data classification as well as for regression problems. The proposed method generates simple rules in a high-level programming language with the help of grammatical evolution. The method does not depend on any prior knowledge...

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Main Author: Ioannis G. Tsoulos
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:AI
Subjects:
Online Access:https://www.mdpi.com/2673-2688/3/3/44
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author Ioannis G. Tsoulos
author_facet Ioannis G. Tsoulos
author_sort Ioannis G. Tsoulos
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description In the current work, a novel method is presented for generating rules for data classification as well as for regression problems. The proposed method generates simple rules in a high-level programming language with the help of grammatical evolution. The method does not depend on any prior knowledge of the dataset; the memory it requires for its execution is constant regardless of the objective problem, and it can be used to detect any hidden dependencies between the features of the input problem as well. The proposed method was tested on a extensive range of problems from the relevant literature, and comparative results against other machine learning techniques are presented in this manuscript.
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spelling doaj.art-e643323b4560402a8d484d4d19bcff082023-11-23T14:39:51ZengMDPI AGAI2673-26882022-09-013375176310.3390/ai3030044Learning Functions and Classes Using RulesIoannis G. Tsoulos0Department of Informatics and Telecommunications, University of Ioannina, 47100 Arta, GreeceIn the current work, a novel method is presented for generating rules for data classification as well as for regression problems. The proposed method generates simple rules in a high-level programming language with the help of grammatical evolution. The method does not depend on any prior knowledge of the dataset; the memory it requires for its execution is constant regardless of the objective problem, and it can be used to detect any hidden dependencies between the features of the input problem as well. The proposed method was tested on a extensive range of problems from the relevant literature, and comparative results against other machine learning techniques are presented in this manuscript.https://www.mdpi.com/2673-2688/3/3/44grammatical evolutiongenetic algorithmsneural networks
spellingShingle Ioannis G. Tsoulos
Learning Functions and Classes Using Rules
AI
grammatical evolution
genetic algorithms
neural networks
title Learning Functions and Classes Using Rules
title_full Learning Functions and Classes Using Rules
title_fullStr Learning Functions and Classes Using Rules
title_full_unstemmed Learning Functions and Classes Using Rules
title_short Learning Functions and Classes Using Rules
title_sort learning functions and classes using rules
topic grammatical evolution
genetic algorithms
neural networks
url https://www.mdpi.com/2673-2688/3/3/44
work_keys_str_mv AT ioannisgtsoulos learningfunctionsandclassesusingrules