Vol. 7, Issue 5, Part C (2021)
Applicability of association rules in finding correlations among covid-19 patient data and importance of fuzzy set theory in predictions
Applicability of association rules in finding correlations among covid-19 patient data and importance of fuzzy set theory in predictions
Author(s)
Reena Hooda
Abstract
The current paper highlight the applicability of association rules in predicting the relation between the different symptoms of Corona and this disease and also the closeness of these symptoms with the reports showing death or cure by the confidence measure and certainty measures. The paper explains the association rule measures like support, confidence, and lift as well as certainty factor to predict the associations among the factors or the attributes of the disease by taking the 3 random rules. The measures successfully predict the ratio between the different symptoms that whether they are dependent to each other, independent or the substitute. The database is a dummy database of patients containing some common symptoms taken from the official site of Centers for Disease Control and Prevention. The paper further emphasizes the importance of set theory and fuzzyfication of the data to get more realistic inferences.
How to cite this article:
Reena Hooda. Applicability of association rules in finding correlations among covid-19 patient data and importance of fuzzy set theory in predictions. Int J Appl Res 2021;7(5):166-169.