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A Novel Corona Virus Detection and Validation Measures using Machine Learning Techniques

G. Dinesh, Dr Ali Mirza Mahmood

Abstract


Data mining is a process of extracting unknown or hidden knowledge from the existing data. This is mainly used for predicting the future based on the past data. Classification in data mining is a common technique that classifies data instances into different classes. It allows you to organize data sets of all sorts, including complex and large datasets as well as small and simple one. Decision tree uses the data to generate sequence of if else rules for decision making. In this paper, we are discussing the pandemic covid-19 related dataset of 1,81,884 instances with 9 attributes. The real world covid-19 data is used to build model to extract the important rules about who had a likely chance to get covid-19 positive. This paper includes one of the algorithms of the decision tree known as C4.5.The experimental results provide are good set of rules for corona virus detection.

Keywords


Data mining, Classification, decision tree, C4.5, Covid19 dataset

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References


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