DataStream Mining is the process of extracting knowledge structures fromcontinuous, rapid data records. Now a day’s huge amount of data is processed& analyzed. so it is very important to classify data & informationproperly. The information is basically unstructured & continuous. Hugevolume of continuous data which has multidimensional feature and often fastchanging. It is required to construct model which adapt such changes & givefast response. Such information flow examples are network traffic, sensor data,call centre records etc. Class evolution is now a day’s important topic in datastream mining which handles such data. So in previous work proposed a modelClass Based ensemble for Class evolution (CBCE) to maintain such a large amount of streams. But for complex &massive data result would be different. so complex class ensemble model (CCEM)is proposed for classification so huge & complex classes can be handled& classify & also proposed a model for class disappearance only so thatmore emphasize on class disappearance than class reoccurrence & novel class
Keywords:- Datastream mining, class evolution, ensemble model, incremental learning.