LAPSE:2021.0567
Published Article
LAPSE:2021.0567
A Genetic Programming Strategy to Induce Logical Rules for Clinical Data Analysis
José A. Castellanos-Garzón, Yeray Mezquita Martín, José Luis Jaimes Sánchez, Santiago Manuel López García, Ernesto Costa
June 21, 2021
This paper proposes a machine learning approach dealing with genetic programming to build classifiers through logical rule induction. In this context, we define and test a set of mutation operators across from different clinical datasets to improve the performance of the proposal for each dataset. The use of genetic programming for rule induction has generated interesting results in machine learning problems. Hence, genetic programming represents a flexible and powerful evolutionary technique for automatic generation of classifiers. Since logical rules disclose knowledge from the analyzed data, we use such knowledge to interpret the results and filter the most important features from clinical data as a process of knowledge discovery. The ultimate goal of this proposal is to provide the experts in the data domain with prior knowledge (as a guide) about the structure of the data and the rules found for each class, especially to track dichotomies and inequality. The results reached by our proposal on the involved datasets have been very promising when used in classification tasks and compared with other methods.
Keywords
clinical data, data mining, evolutionary computation, feature selection, genetic programming, Machine Learning
Suggested Citation
Castellanos-Garzón JA, Mezquita Martín Y, Jaimes Sánchez JL, López García SM, Costa E. A Genetic Programming Strategy to Induce Logical Rules for Clinical Data Analysis. (2021). LAPSE:2021.0567
Author Affiliations
Castellanos-Garzón JA: Department of Computer Science and Automatic, Faculty of Sciences, BISITE Research Group, University of Salamanca, Plaza de los Caídos, s/n, 37008 Salamanca, Spain; CISUC, Department of Computer Engineering, ECOS Research Group, University of Coimbra, P [ORCID]
Mezquita Martín Y: Department of Computer Science and Automatic, Faculty of Sciences, BISITE Research Group, University of Salamanca, Plaza de los Caídos, s/n, 37008 Salamanca, Spain [ORCID]
Jaimes Sánchez JL: Instituto Universitario de Estudios de la Ciencia y la Tecnología, University of Salamanca, 37008 Salamanca, Spain
López García SM: Instituto Universitario de Estudios de la Ciencia y la Tecnología, University of Salamanca, 37008 Salamanca, Spain
Costa E: CISUC, Department of Computer Engineering, ECOS Research Group, University of Coimbra, Pólo II - Pinhal de Marrocos, 3030-290 Coimbra, Portugal
Journal Name
Processes
Volume
8
Issue
12
Article Number
E1565
Year
2020
Publication Date
2020-11-27
Published Version
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr8121565, Publication Type: Journal Article
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LAPSE:2021.0567
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doi:10.3390/pr8121565
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Jun 21, 2021
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Jun 21, 2021
 
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Calvin Tsay
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