CLASSIFICATION USING MACHINE LEARNING ALGORITHMS

ABSTRACT

Breast cancer, a heterogeneous disease in its development and progression, remains the most prevalent female cancer diagnosed worldwide. Breast cancer is the second leading cause of cancer death in women (only lung cancer kills more women each year), and also the most common invasive cancer in women. Awareness of the symptoms are important ways of reducing the risk in order to improve breast cancer outcomes and survival, early detection is critical, the early diagnosis of breast cancer can improve the prognosis and chance of survival significantly, as it can promote timely clinical treatment to patients. Further accurate classification of tumors can prevent patients undergoing unnecessary treatments. Thus, the correct diagnosis of breast cancer and classification of patients into malignant or benign groups is the subject of much research. The purpose of this project is to automate the design of the machine learning algorithms using supervised learning to predict what class data would be. This project therefore diagnosed breast cancer based on symptoms detection. These Symptoms (or dataset) were used to design Machine Learning Application capable of detecting breast cancer correctly. The result of Decision Tree Classifier is that this machine learning algorithm can be used for breast cancer classification. The programming language used to implement these algorithms was Anaconda python.