Accurate Breast Cancer Detection and Classification by Machine Learning Approach

Abstract

In this paper there is comparison of four different machine learning algorithms such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Fuzzy logic and Genetic algorithm on Wisconsin Breast Cancer Diagnosis (WBCD) dataset for the detection of breast cancer in women. The test accuracies are compared to show the efficient algorithm for the detection of breast cancer using those algorithms. The dataset is partitioned to 70% training data and 30% testing data. The results for the applied algorithms are CNN acquired 96.49% accuracy, RNN acquired 63.15% accuracy, fuzzy logic acquired 88.81% accuracy, and genetic algorithm acquired 80.399% accuracy.