Machine learning techniques: Performance analysis for prevalence of heart disease prediction

Abstract

In these days, heart disease has become most dominating problem for medical professionals as well in India and abroad. However, heart disease is a major factor for behind the most of the people deaths today. An efficient and effective machine learning technique is required in order to reduce large scale of deaths due to this problem. In this direction, data mining and machine learning techniques play prominent role for pre-stage detection from heart disease problem. This study focuses on three most important machine learning techniques Support Vector Machine (SVM), Naive Bays (NB) and K-Nearest Neighbor (K-NN) for heart disease prediction. The machine learning tool Statistica is used for result generation purpose. Finally, experimental results stated that SVM method has excellent accuracy (86.12%) over other methods.