Abstract

Abstract: Data Stream Mining is the process of extracting knowledgestructures from continuous and rapid data records arriving at high speed. Stream mining is one of the emerging fields ofresearch in Data Mining. With the growing use of Internet in this digital era,tremendous amount of data is generating exponentially which needs to be analysed.This data is continuous, very large in size and cannot be stored for a longtime. So there is a need to processes the data as soon as it becomes available.Various algorithms are available for mining data from streams, which requiressingle or fewer number of scans. With the recent advancement in Internet ofThings (IOT), huge data streams are generated, thus making stream mining one ofthe most promising area of research. This paper is a review of different Classificationmethods used for data stream mining.

Keywords: DataMining, Data streams, Classification