Active-Passive Clustering

Active-passive clustering is a method for grouping similar data points where one cluster—called the active cluster—drives the formation and updates, continuously adapting as new data arrives. The passive cluster remains relatively stable, serving as a reference or anchor. This approach allows for efficient, scalable clustering especially in large or streaming datasets, as it balances adaptability with stability. The active cluster quickly adjusts to changing patterns, while the passive cluster maintains a steady baseline, resulting in improved accuracy and robustness in identifying meaningful groupings over time.