Predicting Early Possibilities of Breast Cancer Detection Using Machine Learning Techniques

Breast cancer is one of the imperative health concerns affecting women globally, and early diagnosis can help to enhance the prognosis for the cases and patients. The main concern of the current study is to use machine learning algorithms to analyze the dataset of features of breast cancer and predict whether or not they are malignant. In the pre-processing step, we implemented basic steps and on classification steps, we applied several classification algorithms such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and kNearest Neighbor. Among all the classifiers, the Random Forest classifier had the highest estimated accuracy. The paper also brings into prominence the features which are selected and the affect of different sorts of machine learning etc in the diagnosis of the disease.