Review: Approaches for Handling DataStream

Today, there is tremendous use of technology that causes generation of huge volume of data called as Data Stream. Data Stream are continuous, unbounded and usually come with high speed and changes with time. It has different issues such as Memory, Time, Noise, Dynamic data. There is need of handling data streams because of its changing nature, and the data stream may be labelled or it may be unlabelled. Classification is supervised it can only handle labelled data. Thus, there is need of Hybrid Ensemble Classifier in which clustering and classifier are brought together so that the labelled as well as unlabelled datastream both can be handled. This Paper describes different Approaches for Handling DataStream.

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