Abstract: Heart Disease or Cardio Vascular Disease (CVD) is the key factor that leads to majority of deaths across the world from the past, therefore we require accurate and appropriate treatment as well as diagnosis system, and already lot of machine learning techniques is applied on large data sets in medicine field to analyse the data. Many researchers also have been using various machine learning algorithms to help doctors and medical practitioners to Diagnose the Heart diseases. This paper gives the survey of various classification algorithms like Naive Bayes, Support Vector Machines (SVM), Decision Trees (DT), Random Forest (RF) and Logistic Regression (LR) and the execution of the heart data set is depicted using Weka tool.
Keywords: Decision Trees, Heart Disease, Logistic Regression, Random Forest, Support Vector Machines.
| DOI: 10.17148/IJARCCE.2020.9618