A Predictive Modelling for Breast Cancer Classification Using Machine Learning Technique

One of the important health concern all over the globe is Breast Cancer in women. It is a complex disease that requires a thorough diagnosis before treatment can begin. This research paper explores the intervention of AI in treatment of breast cancer leveraged by using data balancing techniques. Using clinical and pathological data, machine learning is a potent tool for predicting its different forms. The effectiveness of several ML algorithms for classification of the same is investigated in this work. Models including Logistic Regression, Support Vector Machines etc. were trained and evaluated on a dataset with pertinent attributes. Some of the evaluation metrics were used to assess the models. Logistic Regression and AdaBoost classifier gave the most accurate outcome with an accuracy of 0.98 and outperformed other models. Efficacy of the models were supported by providing ROC curve of all models and confusion matrix of the best performing models.