Software defect prediction using cost-sensitive neural network
Software defect prediction model was built by Artificial Neural Network (ANN). ANN connection weights were optimized by Artificial Bee Colony (ABC). Parametric cost-sensitivity feature was added to ANN by using a new error function. Model was applied to five publicly available datasets from the NASA repository. Results were compared with other cost-sensitive and non-cost-sensitive studies.
software defect prediction artificial neural network artificial bee colony machine learning software quality cost-sensitive classification