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Neuronal Communication Genetic Algorithm-Based Inductive Learning

Auteurs: » ALAOUI Abdiya
Type : Revue Internationale
Nom du journal : Journal of Information Technology Research (JITR) ISSN:
Volume : 13 Issue: 2 Pages: 141-154
Lien : »
Publié le : 01-04-2020

The development of powerful learning strategies in the medical domain constitutes a real challenge. Machine learning algorithms are used to extract high-level knowledge from medical datasets. Rule-based machine learning algorithms are easily interpreted by humans. To build a robust rule-based algorithm, a new hybrid metaheuristic was proposed for the classification of medical datasets. The hybrid approach uses neural communication and genetic algorithm-based inductive learning to build a robust model for disease prediction. The resulting classification models are characterized by good predictive accuracy and relatively small size. The results on 16 well-known medical datasets from the UCI machine learning repository shows the efficiency of the proposed approach compared to other states-of-the-art approaches.

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