In this study, we propose a new method to enhance the accuracy of Modified Multi-class Classification based on Association Rule (MMCAR) classifier. We introduce a Partial Rule Match Filtering (PRMF) method that allows a minimal match of the items in the rule’s body in order for the rule to be added into a classifier. Experiments on Reuters-21578 data sets are performed in order to evaluate the ...

In this paper, the relation among factors in the road transportation sector from March, 2005 to March, 2011 is analyzed. Most of the previous studies have economical point of view on gasoline consumption. Here, a new approach is proposed in which different data mining techniques are used to extract meaningful relations between the aforementioned factors. The main and dependent factor is gasolin...

This project [4] centers on regional association rule mining and scoping in spatial datasets. We introduces a methodology for mining spatial association rules and proposes new algorithms to determine the scope of a spatial association rule. We develop a reward-based region discovery framework that employs clustering to find interesting regions. The framework is applied to solve two distinct reg...

Association rule mining is the process of finding some relations among the attributes/attribute values of huge database based on support value. Most existing association mining techniques are developed to generate frequent rules based on frequent itemsets generated on market basket datasets. A common property of these techniques is that they extract frequent itemsets and prune the infrequent it...