The performance measures were described in terms of mean squared errors, classification accuracies, sensitivities, specificities, the area under the curve, and receiver operating characteristic curve. It was found that IMGWO outperformed three popular metaheuristic approaches including GWO, genetic algorithm, and particle swarm optimization. Results confirmed the potency of IMGWO as a viable learning technique for an ANN |