A Review of Cluster Oriented Ensemble Classifier for Improving Performance of Stream Data Classification

Abstract

Ensemble classification technique is great advantage over conventional classifier such as statistical, binary and neural network classifier. Ensemble technique improves the performance of other classifier with some valid constraints. In the improvement of ensemble classifier cluster play important role for data grouping before classification. Cluster oriented ensemble classifier maintain and control the diversity of data during classification process. The diversity of cluster oriented ensemble classifier implied in stream data classification. Stream data classification is critical task due to diversity of data. The critical task of diversity such as infinite population, data drift and feature evaluation technique is overcome through ensemble classifier. Various author proposed a method for stream data classification using ensemble technique. In this paper we give the review of ensemble technique used in stream data classification with clustering technique.