Abstract:
The performance of the models were evaluated using a number of
known standard evaluation metrics such as precision, recall, and f-measure. In particular, this research
work shows that decision tree, naïve bayes, support vector machine (OneVsOne) and k-nearest neighbor’s
classifier algorithms had performance accuracy of (88.3%), (83%), (98.0%), (98.8%) respectively and
when we came to neural network algorithm artificial neural network had performance accuracy of (99.4%).
From our experiments the obtained results show a good performance and this shows that it is possible to
design effective and efficient model that predict the risk of having cardiovascular disease
