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Mining Discrimination Patterns along Temporal Databases

In certain Data Analysis tasks, understanding the underlying differences between groups or classes is of the utmost importance. Contrast Set Mining relies on discovering significant patterns by contrasting two or more groups. A Contrast Set is a conjunction of attribute-value pairs that differ meaningfully in its distribution across groups. One technique proposed is Rules for Contrast Sets (RCS) which seeks to express each Contrast Set found in terms of rules. The main purpose of this work is to extend RCS to a Temporal Data Mining task. We define a set of temporal patterns in order to capture the significant changes in the contrasts discovered along the considered time line. To ascertain the proposal accuracy and ability to discover relevant information, two different real-life datasets were studied using this approach.