Genetic Algorithm-Neural Network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection

• Published in: International journal of machine learning and cybernetics Vol. 1; no. 1-4; pp. 75 - 87
• Main Authors: Tong, Dong Ling, Mintram, Robert
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.12.2010; Springer Nature B.V
• Subjects: Artificial Intelligence; Artificial neural networks; Chromosomes; Classifiers; Complex Systems; Computational Intelligence; Control; Datasets; Engineering; Genetic algorithms; Hybrid systems; Hyperbolic functions; Machine learning; Mechatronics; Neural networks; Optimization; Original Article; Pattern Recognition; Robotics; Systems Biology; GA population; Feature selection; Genetic Algorithm (GA); Activation function; GA evaluation; Artificial Neural Network (ANN)

Hybrid genetic algorithms (GA) and artificial neural networks (ANN) are not new in the machine learning culture. Such hybrid systems have been shown to be very successful in classification and prediction problems. However, little attention has been focused on this architecture as a feature selection...