Breast Cancer Diagnosis Using MLP Back Propagation
International Journal of Emerging Trends in Engineering Research · 2020
Breast Cancer (BC) is one of the most prevalent forms of Cancer among women.Premature diagnosis of BC is crucial to the survival of the patient.Here we implement an algorithm designed to diagnose and forecast breast cancer using a multi-layer perceptron (MLP) back-propagation technique that will help doctors diagnose the disease (benign, malignant).The proposed MLP includes an input layer, and, has inputs linked to the ten attributes of the data set.It has a hidden layer with five nodes (neurons).It leads to the pair outcomes: benign and malignant.The objective of our projected algorithm is to diagnose and classify the disease.MLP can help timely recognition of the cancer, and, therefore, can help to go for proper medication at early stage of cancerous development.This approach is tested on the (WBC) Wisconsin Breast Cancer dataset, resulted in 98.9 percent accuracy of classification using MLP back propagation.