Association Rule Generation Using Apriori Mend Algorithm for Student's Placement
The association rules are used to find interesting rules from large collections of data which expresses an association between items or sets of items. The usefulness of this technique is to address typical data mining problems is best. In order to show the effective relation of data, student placement was chosen and experiments were carried out which shows the best rules with 92.86% confidence while comparing with the previous Apriori approach. In this paper, Apriori Mend algorithm was discussed which provide better result in mining association rules for Student's placement in industry.