Prognosis of Cardiovascular Disease using Machine Learning Approach

Abstract

This paper presents a machine learning model that will detect cardiovascular disease at the early stage. Machine learning is an effective tool, assisting in making decision and predictions from the large quantity of data. The proposed machine learning algorithms-based prediction model works with different combination of features and known classification technique to analyze the dataset. The dataset consists of 11 attributes and a target attribute to performing the analysis, where the model begins with the pre-processing phase and selects the most relevant features in the dataset, it applies Random Forest algorithm and got the high accuracy compared to other popular classifiers, Also Proposed model uses multiple trees as a result there is no overfitting problem. And its training time is less and run efficiently on larger database.