Breast Cancer Prediction using CNN and Machine Learning Algorithms with Comparative Analysis

At present world, Breast cancer is a second main cause of cancer death in women after lung cancer. Breast cancer occurs when some breast cells begin to raise abnormally. It can arise in any portion of the Breast and it can be prevented if the treatment is started at the early stage of the Breast cancer. Breast cancer is a malignant tumour i.e. a collection of cancer cells arising from the cells of the breast Treatment of breast cancer relies on the cancer type and its stage. Mainly this paper focused on diagnosing the Breast cancer disease using various classification algorithm with the help of data mining tools. Data mining of the intelligent accumulated from previously disease detected patients opened up a new aspect of medical progression In this paper, the focus has been prediction of breast cancer using various machine learning algorithms and visualizing the performances of each algorithm. This paper makes use of a dataset that contains numerical values about the clump thickness, uniformity of the cell for prediction using Multi Layer Perceptron, K-NN, Random Forest, Logistic Regression. Moreover, this also uses a dataset of tissue images for the prediction using Convolution Neural Network. Later, the accuracies of each algorithm is calculated along with the precision, recall, f-score, ROC for each algorithm.