作者
Sanjeev Kumar Punia, Manoj Kumar, Thompson Stephan, Ganesh Gopal Deverajan, Rizwan Patan
发表日期
2021/7/1
期刊
International Journal of E-Health and Medical Communications (IJEHMC)
卷号
12
期号
4
页码范围
60-75
出版商
IGI Global
简介
In broad, three machine learning classification algorithms are used to discover correlations, hidden patterns, and other useful information from different data sets known as big data. Today, Twitter, Facebook, Instagram, and many other social media networks are used to collect the unstructured data. The conversion of unstructured data into structured data or meaningful information is a very tedious task. The different machine learning classification algorithms are used to convert unstructured data into structured data. In this paper, the authors first collect the unstructured research data from a frequently used social media network (ie, Twitter) by using a Twitter application program interface (API) stream. Secondly, they implement different machine classification algorithms (supervised, unsupervised, and reinforcement) like decision trees (DT), neural networks (NN), support vector machines (SVM), naive Bayes (NB …
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