Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Hybrid Genetic Algorithms for Feature Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining and Knowledge Discovery
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Neural networks for classification: a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A novel learning scheme for Chebyshev functional link neural networks
Advances in Artificial Neural Systems
Functional link neural network: artificial bee colony for time series temperature prediction
ICCSA'13 Proceedings of the 13th international conference on Computational Science and Its Applications - Volume 1
International Journal of Business Intelligence and Data Mining
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This paper proposed a hybrid functional link artificial neural network (HFLANN) embedded with an optimization of input features for solving the problem of classification in data mining. The aim of the proposed approach is to choose an optimal subset of input features using genetic algorithm by eliminating features with little or no predictive information and increase the comprehensibility of resulting HFLANN. Using the functionally expanded selected features, HFLANN overcomes the non-linearity nature of problems, which is commonly encountered in single layer neural networks. An extensive simulation studies has been carried out to illustrate the effectiveness of this method over to its rival functional link artificial neural network (FLANN) and radial basis function (RBF) neural network.