HEART DISEASE CLASSIFICATION USING MACHINE LEARNING TECHNIQUES. Issue 1 (June 2021)

• Record Type: Journal Article
• Authors: Radhika, R.; Thomas George, S.
• Is Part Of: Journal of physics. Volume 1937:Issue 1(2021)
• Publication Date: 2021-06
• Subjects: Heart disease -- Machine learning -- K-Nearest Neighbour -- Support Vector Machine -- Naïve Bayes -- logistic regression -- decision tree algorithm -- random forest algorithm; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1937/1/012047
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Heart disease is one of the Leading reason for death around the world. In which machine learningis a method that predicts the emerging prospects of Heart Disease. Machine learning is used in taking care of numerous issues in information science. The basic utilization of machine learning is the forecast of a result dependent on already existing information. The machine takes the designs from the current dataset, and it is applied on an obscure dataset to foresee the result. Order method in AI is usually used for expectation. Some arrangement calculations foresee with acceptable precision, while others show a restricted exactness. Here, we play out an order dependent on various arrangement calculations like K-Nearest Neighbour, Support Vector Machine, Naïve Bayes, logistic regression, decision tree algorithm and random forest algorithm