Breast Cancer is the second most dangerous cancer in the world. Most of the women die due to breast cancer not only in India but everywhere in the world. In 2011, USA stated that one in eight women suffered from cancer. Breast cancer develops due to the abnormal cell division in the breast itself which results in the formation of either benign or malignant cancer. So, it is very important to predict breast cancer at an early stage and by providing proper treatment, many lives can be saved. This paper aims to give a comparative study by applying different machine learning algorithms such as Support Vector Machine, K-Nearest Neighbour, NaÃ¯ve Bayes, Decision Tree, K-means and Artificial Neural Networks on Wisconsin Diagnostic dataset to predict breast cancer at an early stage.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL