Accuracy Extended Ensemble - A Brood Purposive Stream Data mining

The objective of Data mining is to haul out knowledge from gigantic quantity of data. The storage, querying and mining of such data sets are highly computationally challenging tasks. Mining data streams is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information. The research in data stream mining has gained a high attraction due to the importance of its applications and the increasing generation of streaming information. Decision trees have been widely used for online learning classification.In this article the problem of data-stream classification has been considered by introducing an online and incremental stream-classification ensemble algorithm given name Accuracy Extended Ensemble which an extension to the Accuracy Weighted Ensemble.Proposed algorithm will be adept to deal with data streams having an evolving nature and an ergodic arrival rate of training/test data records