Classification of Concept Drift Data Streams

Concept drift has been a very important concept in the realm of data streams. Streaming data may consist of multiple drifting concepts each having its own underlying data distribution. Concept drift occurs when a set of examples has legitimate class labels at one time and has different legitimate labels at another time. This paper provides a comprehensive overview of existing concept -evolution in concept drifting techniques along different dimensions and it provides lucid vision about the ensemble's behavior when dealing with concept drifts.