The Perspicacity of Association Rule Mining in the Multifaceted Environment of Ayurveda

Background: A number of Data mining techniques are used to decode the concealed knowledge. Among them, Association Rule Mining facilitates to find out interesting associations amid the attribute conditions and class labels and thereby aid in decision making. In Ayurveda, the formulations are designed by taking into consideration a varied number of aspects which leads to the generation of a multifaceted environment. This is clearly depicted in the Mishrag varga mentioned in the classics of Ayurveda. Objective: So, the present study was conducted to find out significant relationships between the drug combinations and the action manifested with the help of Association Rule Mining. Method: The therapeutic effects exerted by the two mishrag varga viz. Panchkola and Shadushna were taken into the study and then association rules were generated in RStudio 0.99.485 using Apriori algorithm implemented in arulesViz, which is an R-extension package. Result: Ten rules were generated which evidently support the properties of the two groups quoted in the classics. Conclusion: It was thus concluded that the association rules give a perspicacious view of the visionary associations and also edify the Drug discovery logic prevalent in the multifaceted environment of Ayurveda.