Prediction of Arrhythmia with Machine Learning Algorithms
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The present study uses the age, sex, diabetes mellitus, and arrhythmia data of patients from the datasets presented in an existing study to predict arrhythmia with machine learning algorithms, K-Nearest Neighbors (KNN), and Naive Bayes methods. The outputs are schematically presented, and the conclusions related to the Bayes theorem and KNN algorithms are compared. In the case of increasing the value of neighboring k in the KNN method, it is seen that the accuracy rate approaches the result obtained from the Naive Bayes method.
Açıklama
9th International Symposium on Digital Forensics and Security (ISDFS) -- JUN 28-29, 2021 -- Fırat Univ, Elazig, TURKEY
Anahtar Kelimeler
Arrhythmia, Diabetes Mellitus, Bayes Theorem, K-Nearest Neighbors
Kaynak
9th International Symposium on Digital Forensics And Security (Isdfs'21)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
