Breast cancer is one of the major causes of death in women when compared to all other cancers. Breast cancer has become the most hazardous types of cancer among women in the world. Early detection of breast cancer is essential in reducing life losses. This paper presents an approach for identifying breast cancer using classification algorithm. This project comprises of three modules user module which user can enter the details once they have enter the details an unique id will be generated to each user .The user will authenticate based on their credentials. The patient enters his patient id; a message box will be prompting them to view the results after the process complete. The second module is classification module in which individual observations are analyzed into set properties. These properties may variously to user to user. Based on that training dataset the test data will assign to the specific category. Third module is prediction module in which the result will be predicted at the last stage with the help of SVM. We compare classification techniques in Waikato Environment for Knowledge Analysis (weka) software and comparison results with the help of Support Vector Machine (SVM) The SVM will predict the result with based on the risk score once the result is predicted it is stored, so that the user can view the result. This project is implemented in java as the front end and mysql as the back end. This project aims to implement an effective prediction on breast cancer using classification algorithm .with the help of it the user can know the cancer status. From this project we infer that the SVM are more suitable in handling the classification problem of breast cancer prediction
