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.
Requires login.
Related Concepts (1)
Similar Concepts
- anomaly detection
- anomaly detection techniques
- behavioral analysis and anomaly detection
- bias detection
- causal discovery
- causal explanations
- concept formation
- conceptual analysis
- detection efficiencies
- explanatory gap
- fault detection
- fault detection and diagnosis
- knowledge diffusion
- knowledge discovery
- object detection