Please cite at least one of the following papers if you like to use the works: Jan, Z.M. and Verma, B., 2019, June. Ensemble Classifier Optimization by Reducing Input Features and Base Classifiers. In 2019 IEEE Congress on Evolutionary Computation (CEC) (pp. 1580-1587). IEEE.

Jan, Z.M., Verma, B. and Fletcher, S., 2018, July. Optimizing clustering to promote data diversity when generating an ensemble classifier. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1402-1409). ACM.

How to use You should run the mainprogram.m file

Dataset Datasets are already placed in the DTE folder short for Data Training Environment. All datasets are directly downloaded from UCI repository and are converted to MAT files. 10-fold cross validated folds are already created so to speed up the training process. This work uses Matlabs builtin GAOPtimization Toolbox, and NeuralNetwork toolbox.