Evaluation of quality measures for contrast patterns by using unseen objects

• DOI: 10.1016/j.eswa.2017.04.038
• Publication Date: 2017-04-19T04:00:46Z
• Authors: Milton García-Bor...; Octavio Loyola-Go...; José Fco. Martíne...; Jesús Ariel Carra...
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

We propose estimating the quality of a contrast pattern using unseen objects.We evaluate quality measures by correlating their values and the estimated quality.We describe the influence of database characteristics in correlations.We perform a study to find how to synergistically combine quality measures. Contrast patterns, which lie in the core of most understandable classifiers, are frequently evaluated by quality measures. Since many different quality measures are available, they should be compared to select the most appropriate for each applications. This paper introduces a method to compare quality measures, using a set of mined patterns and a collection of objects not used for mining. The comparison is performed by correlating quality values with a quality estimation of the patterns. Additionally, a meta-learning study is performed to show that combining quality measures could be better than using the best single measures in isolation. The results of this paper can help researchers to create new quality measures or to find new combinations of quality measures to create better understandable classification systems.