• Manali
• Neeshu Kumari

Background: Disease Prediction framework dependent on prescient displaying predicts the infection of the client based on the indications that client gives as a contribution to the framework. The framework examines the indications gave by the client as info and gives the likelihood of the ailment as a yield. Ailment Prediction is finished by actualizing 5 systems, for example, Naïve Bayes, KNN, Decision Tree, Linear Regression and Random Forest Algorithms. Aim: To study different ML algorithms to predict diseases related to heart through using considering various issues such as accuracy and precision. Results: Random Forest algorithm outperforms from all the algorithms with accuracy around 88%.

Machine learning, Algorithms, Diseases related to Heart

"Ameliorate Performance of Predicting Diseases Related to Heart by Utilizing ML Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 7, page no.1027-1031, July-2020, Available :http://www.jetir.org/papers/JETIR2007127.pdf

"Ameliorate Performance of Predicting Diseases Related to Heart by Utilizing ML Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp1027-1031, July-2020, Available at : http://www.jetir.org/papers/JETIR2007127.pdf