BREAST CANCER PREDICTION USING MACHINE LEARNING APPROACHES

In recent days the fast-growing disease in most of the world's is breast cancer especially in women and, according to global statistics, represents a different level of cases that are hitting cancer and illnesses associated with related diseases, rendering it a major public health issue currently in the community. The diagnosis and treatment for this significantly contributed by the machine learning techniques that can be applied for patient data to detect the cancer stage at earlier stages can help patients receive appropriate medical treatment. In this paper, four classification methods have been used in the context of Bayes Net, Adaboost, Simple Logistic and Stochastic Gradient Descent, successfully. The primary goal is to test in terms of accuracy, uncertainty matrix, MAE and RMSE, consistency in the identification of information concerning efficiency and effectiveness of each algorithm.