Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
Abstract. In the literature of data mining and statistics, numerous interestingness measures have been proposed to disclose succinct object relationships of association patterns. H...
This paper proposes a fault-prone module prediction method that combines association rule mining with logistic regression analysis. In the proposed method, we focus on three key m...
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for ...
Abstract. We propose a formal definition of the robustness of association rules for interestingness measures. It is a central concept in the evaluation of the rules and has only be...
Yannick Le Bras, Patrick Meyer, Philippe Lenca, St...