Design of Ensemble Classifier Model Based on MLP Neural Network For Breast Cancer Diagnosis

Nowadays, breast cancer is one of the leading causes death women in worldwide. If detected at beginning stage, it can ensure long-term survival. Numerous methods have been proposed for early prediction this cancer, however, efforts are still ongoing given importance problem. Artificial Neural Networks (ANN) established as some most dominant machine learning algorithms, where they very popular and classification work. In paper, an Intelligent Ensemble Classification method based on Multi-Layer Perceptron neural network (IEC-MLP) diagnosis. The split into two stages, parameters optimization ensemble classification. first MLP Network (MLP-NN) parameters, including optimal features, hidden layers, nodes weights, optimized with Evolutionary Algorithm (EA) maximize accuracy. second algorithm MLP-NN applied to classify patient parameters. Our IEC-MLP which not only help reduce complexity effectively selection feature subset, but also obtain minimum misclassification cost. results were evaluated using different datasets obtained promising (98.74% accuracy WBCD dataset). Meanwhile, outperforms GAANN CAFS algorithms other state-of-the-art classifiers. addition, could be