% Benchmark data set
load ionosphere.mat;
% Set 20% data as validation set
ho = 0.2;
% Hold-out method
HO = cvpartition(label,'HoldOut',ho);
% Parameter setting
N = 10;
max_Iter = 100;
% Binary Grey Wolf Optimization
[sFeat,Sf,Nf,curve] = jBGWO2(feat,label,N,max_Iter,HO);
% Plot convergence curve
plot(1:max_Iter,curve);
xlabel('Number of Iterations');
ylabel('Fitness Value');
title('BGWO2'); grid on;
@article{too2018new,
title={A new competitive binary Grey Wolf Optimizer to solve the feature selection problem in EMG signals classification},
author={Too, Jingwei and Abdullah, Abdul Rahim and Mohd Saad, Norhashimah and Mohd Ali, Nursabillilah and Tee, Weihown},
journal={Computers},
volume={7},
number={4},
pages={58},
year={2018},
publisher={Multidisciplinary Digital Publishing Institute}
}
@article{too2020opposition,
title={Opposition based competitive grey wolf optimizer for EMG feature selection},
author={Too, Jingwei and Abdullah, Abdul Rahim},
journal={Evolutionary Intelligence},
pages={1--15},
year={2020},
publisher={Springer}
}