Description
Rapidly growing URBAN lifestyle makes us unhealthy and various health-relevant risk has increased. among different kinds of disease risks, heart disease is much common. the risk of heart disease can be identified by different lifestyle and medical features. additionally we can also learn these features using some decision-making algorithms to predict the risk of heart disease. In this presented work a data mining model for heart disease prediction is proposed and implemented. the model includes three decision tree algorithms namely ID3, C4.5, and CART decision tree. the experiments with real-world data sets available at UCI and Kaggle have been carried out. the experimental results demonstrate ……,
Reviews
There are no reviews yet.