An evolutionary algorithm for clustering data stream is proposed.
Our algorithm allows estimating k automatically from the data in an online fashion.
It monitors eventual degradation in the quality of the induced clusters.
Results show our algorithm correctly detects, and react to, changes in a data stream.
The proposed method is very competitive in terms of accuracy and time processing.