Classification and Prediction of Breast Cancer using Linear Regression, Decision Tree and Random Forest

Breast Cancer is one of a major issue that some of the women are facing today. Earlier detection of cancer by performing detailed analysis based on the existing records which may assist the physicians in providing a better treatment to their patients. Data to analyze and predict the breast cancer are obtained from UCI Machine Learning Repository (Wisconsin Breast Cancer). The main objective is to classify whether the type of cancer is benign or malignant. Based on the available data set and the patient record, whether the disease is curable or non-curable is predicted. Thus the success rate of classification is 84.14% and the prediction percentage is 88.14%.