A novel approach for statistical and fuzzy association rule mining on quantitative data
G. Vijay Krishna, Pisipati Radha Krishna · Journal of Scientific & Industrial Research · 2008
This paper presents a method for deriving Association rules by using apriori algorithm, clustering and fuzzy set concepts. Association rules of quantitative data are presented with mean and standard deviation, and with fuzzy linguistic terms. A case study was done on the commodity data to demonstrate vitality of proposed method. The statistical and fuzzy Association rules, inferred from the commodity data set, are helpful for the business experts in exporting related commodities to a set of countries in a more effective way along with high profits.