Prediction of arrhythmia from MIT-BIH database using random forest (RF) and voted perceptron (VP) classifiers

• Published in: AIP conference proceedings Vol. 2822; no. 1
• Main Authors: Vinutha, K., Thirunavukkarasu, Usharani
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 14.11.2023
• Subjects: Algorithms; Arrhythmia; Cardiac arrhythmia; Classification; Classifiers; Data mining; Machine learning; Software; Statistical analysis

The main purpose of the study is to predict arrhythmia from the MIT-BIH database using Random Forest (RF) and Voted Perceptron (VP) classifiers. Materials and Methods: The proposed study uses the RF and VP Machine learning Algorithms to predict the arrhythmia using MIT-BIH dataset with healthy (n=65...