Logistic and Softmax Regression for Prognosis & Diagnosis of Breast Cancer Using Multilayered Neural Networks

Abstract

Presently Breast Cancer is spiking as 3rd most dangerous cancer in the world. Breast Cancer has become the wide known epidemic as it occurs in all ages of women from adult to old ones too. The malignant tumor is the main cause, which is very hard to even identify with mammography & human discretion. Thus, advancement in technological researches have become a winning factor as Machine Learning and Artificial Neural Networks are helping researchers and doctors worldwide. The valuation of prediction is being done by using algorithms like Logistic Regression and SoftMax Regression to train models with data set Wisconsin Breast Cancer Data of UCI Machine Learning Repository. To perform all of these operations we have used Google Colab (Jupyter notebook backed by Python 3.x). The proposed work results into trained neural network model which is having much better accuracy when compares to the other pre-existing models.