concept drift detection and explanations

Concept drift detection refers to the process of identifying and recognizing changes in patterns or concepts within a particular dataset. It involves actively monitoring and detecting shifts in data distribution or relationships over time. Explanations in concept drift detection involve understanding and interpreting the reasons or causes behind the detected drift, providing insights into why the changes occurred. It helps analysts and researchers to gain better understanding and adjust their models or systems to accommodate the evolving data dynamics.

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