Comparison of Correlated Algorithm Accuracy Naive Bayes Classifier and Naive Bayes Classifier for Classification of heart failure
نویسندگان
چکیده
Heart failure (ARF) is a health problem that has relatively high mortality and morbidity rates in developed or developing countries, including Indonesia. In 2016, WHO stated 17.5 million people died from cardiovascular disease, while 2008, HF disease represented 31% of patient deaths worldwide. One the new breakthroughs for early diagnosis utilizing data mining techniques. this study, Correlated Naive Bayes Classifier (C-NBC) (NBC) algorithms are used to obtaining best accuracy results so they can be Failure dataset. Based on tests have been carried out, it shows algorithm 80.6% obtains higher than 67.5%. With use diagnose patients with heart (heart failure) because level categorized as Good Classification.
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ژورنال
عنوان ژورنال: Ilkom Jurnal Ilmiah
سال: 2022
ISSN: ['2087-1716', '2548-7779']
DOI: https://doi.org/10.33096/ilkom.v14i2.1148.120-125