World Covid-19 Vaccine Names Classification Using Neural Network Method

Kristiawan Nugroho
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Abstract

The Covid-19 pandemic has occurred for a year on earth. Various attempts have been made to overcome this pandemic, especially in making various types of vaccines developed around the world. The level of vaccine effectiveness in dealing with Covid-19 is one of the questions that is often asked by the public. This research is an attempt to classify the names of vaccines that have been used in various nations by using one of the robust machine learning methods, namely the Neural Network. The results showed that the Neural Network method provides the best accuracy, which is 99.9% higher than the Random Forest and Support Vector Machine(SVM) methods.
基于神经网络方法的全球Covid-19疫苗名称分类
Covid-19大流行已经在地球上发生了一年。为克服这一流行病已作出各种努力,特别是在世界各地研制各种类型的疫苗。应对Covid-19的疫苗有效性水平是公众经常提出的问题之一。这项研究是试图使用强大的机器学习方法之一,即神经网络,对各国使用的疫苗名称进行分类。结果表明,神经网络方法的准确率最高,比随机森林和支持向量机(SVM)方法提高了99.9%。
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