Extraction of Association Rules from Education Data

Abstract

Data mining concerns with developing methods for discovering knowledge from data that come from educational environment. This paper presents finding interesting patterns from educational database. Association rule mining is used to find the interesting patterns.Two important measures 'support' and 'confidence' are used to measure the interestingness of the patterns.Since support and confidence are not enough to measure the relationships of itemset. The statistical index of the degree to which two variables are associated is the correlation coefficient and it is measured by lift ratio. Extracting the most interesting association rules can be quite tricky. One of the difficulties is that many measures of interestingness do not work effectively for all datasets. In this paper, correlation ratios of association rules are used to measure the interestingness. The lift value of rule, greater than 1, indicates a positive correlation between antecedent and consequent.