A Review of Data Classification Using various Classifiers Algorithm

Machine-Learning (ML) methods have great importance in interdisciplinary domains. Besides many areas, healthcare domain is the most thriving area where the involvement of Machine Learning algorithms is relatively essential. The purpose of this research is to put together the various supervised learning algorithms such as Logistic Regression, Random Forest, XG boost and Support Vector Machine for the prediction of heart disease by considering relevant medical parameters in the dataset. It uses the training dataset to get better boundary conditions which could be used to determine each target class. Once the boundary conditions are determined, the validation will be done to predict the target class.The system also analyses the performance metrics of the algorithms in order to compare their effectiveness in real-time.