Amelioratethe Accuracy rate of Heart disease Predictionusing Robust models of Machine Learning

Author(s)	Ms. Pratibha Priya Gundabathina
Country	India
Abstract	In Present days after the COVID pandemic the heart diseases risks are growing throughout the world not only in the aged persons but also occurred in teenagers. It is very much needful requirement in the real world to predict the symptoms of heart diseases in advance before they attack the human body. Previously several researchers are trying to identify the heart disease occurred in human body in advance. In this process Machine learning algorithms are very much helpful to the researchers because those algorithms or models can be applied on the different data sets and observe the predicting accuracy in different dimensions. In this paper researcher used the SVM (Support Vector Machine), KNN (K nearest Neighbor) and Naive Bayes machine learning algorithms to improve the predicting accuracy of heart disease affected rate.
Keywords	Heart rate, Heart Disease, Prediction Accuracy, Robust models, Accuracy rate, Machine learning algorithms
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-08-13
DOI	https://doi.org/10.71097/IJSAT.v16.i3.7758
Short DOI	https://doi.org/g9w9qt

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