Introduction

Input

Output

Example

% Benchmark data set load ionosphere.mat;% Set 20% data as validation setho = 0.2; % Hold-out methodHO = cvpartition(label,'HoldOut',ho);% Parameter settingN        = 10; max_Iter = 100; % Whale Optimization Algorithm[sFeat,Sf,Nf,curve] = jWOA(feat,label,N,max_Iter,HO);% AccuracyAcc = jKNN(sFeat,label,HO); fprintf('\n Accuracy: %g %%',Acc); % Plot convergence curveplot(1:max_Iter,curve); xlabel('Number of Iterations');ylabel('Fitness Value');title('WOA'); grid on;

Requirement

Cite As

@article{too2021spatial,  title={Spatial bound whale optimization algorithm: an efficient high-dimensional feature selection approach},  author={Too, Jingwei and Mafarja, Majdi and Mirjalili, Seyedali},  journal={Neural Computing and Applications},  pages={1--22},  year={2021},  publisher={Springer}}