Obtaining optimal quality measures for quantitative association rules

Obtaining optimal quality measures for quantitative association rules

There exist several works in the literature in which fitness functions based on a combination of weighted measures for the discovery of association rules have been proposed. Nevertheless, some differences in the measures used to assess the quality of association rules could be obtained according to the values of the weights of the measures included in the fitness function. Therefore, user's dec...

Some Quality Measures for Fuzzy Association Rules

Several approaches generalizing crisp association rules to fuzzy association rules have been proposed. In an our previous paper we introduced a pair of confidence measures for crisp association rules from which one can be obtained the majority known quality measures. In this paper, starting from these results we give an extension to fuzzy association rules.

ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

There exist several fitness function proposals based on a combination of weighted objectives to optimize the discovery of association rules. Nevertheless, some differences in the measures used to assess the quality of association rules could be obtained according to the values of such weights. Therefore, in such proposals it is very important the user’s decision in order to specify the weights ...

A Clear View on Quality Measures for Fuzzy Association Rules

Selecting the best measures to discover quantitative association rules

The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate the quality of the rules obtained. However, these two measures may not be sufficient to properly assess their quality due to some inherent drawbacks they present. A review of the literature reveals that there exist many measures to evaluate the quality of the rules, but tha...