Open AccessHEART DISEASE CLASSIFICATION USING MACHINE LEARNING TECHNIQUES
Author(s) -
R. Radhika,
S. Thomas George
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1937/1/012047
Subject(s) - machine learning , decision tree , support vector machine , naive bayes classifier , artificial intelligence , random forest , computer science , logistic regression , order (exchange) , tree (set theory) , data mining , mathematics , mathematical analysis , finance , economics
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