Real life business processes change over time, in both planned and unexpected ways. These changes over time are called concept drifts and its detection is a big challenge in process mining since the inherent complexity of the data makes difficult distinguishing between a change and an anomalous execution. The following logs were generated synthetically in order to prove the quality of different concept drift detection algorithms.
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