Breast Cancer Classification using Nature-inspired Algorithm

Abstract

Breast Cancer is one among the dangerous ailments that roots up of deaths among women worldwide. Lots of risk factors have been identified through research though the exact reasons of breast cancer are not yet fully understood The Artificial Immune Recognition System classifier helps to classify the type of breast cancer on Wisconsin dataset which provides accurate prediction of the classes of breast cancer. i.e, Benign and Malignant. This system focuses on supervised classification with the help of clonal selection algorithm, Hierarchical Learning Vector Quantization, Multipass Self Organizing Map. The goal of this system can implement the algorithm to classify the cancer accurately and to compare the error rate, f-measure with previous classification algorithms.