An Effective Performance Analysis of Machine Learning Techniques for Cardiovascular Disease

摘要: Machine learning techniques will help in deriving hidden knowledge from clinical data which can be of great benefit for society, such as reduce the number trials required precise diagnosis a disease person etc. Various areas study are available healthcare domain like cancer, diabetes, drugs This paper focuses on heart dataset and how machine understanding level risk associated with diseases. Initially, is preprocessed then analysis done two stages, first stage feature selection applied 13 commonly used attributes second 75 related to anatomic structure blood vessels heart, arteries Finally, validation reduced set features using an exhaustive list classifiers done.In parallel anatomy identified characteristics each class understood. It observed that these anatomically relevant. Thus, it concluded that, applying beneficial necessary.