Heart related disease is one of the crucial reasons for high amount of people’s death in the whole countries and it’s considered as life forbidding disorder, in addition to that this effect takes place in whole earth. Heart disease will affect the early stage of age peoples also. Thus, heart related disease creates the more challenges to people living and identify the causes and detection step is more important in nowadays. So, we need to develop of automatic system with more accurate and reliable for early detection of heart disease. For this reason, various machine learning models are developed to predict heart related disease; different medical data package is processed to automatic analysis with get more accuracy. In this paper, we discuss the available machine learning models such as KNN, SVM, DT and RF algorithms for prognosis of heart disease with high certitude, precision and recall.
CITATION STYLE
N, Arunpradeep., & Niranjana, Dr. G. (2020). Different Machine Learning Models Based Heart Disease Prediction. International Journal of Recent Technology and Engineering (IJRTE), 8(6), 544–548. https://doi.org/10.35940/ijrte.f7310.038620
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