A Review on Feature Selection Data Stream Mining in Big Data

Computer Engineering

Though the Big Data has many challenges that face both commercial IT deployment and academic research communities, the Big Data have many root sources and that are founded on data stream and annoyance of dimensionality. In the field of Big data Network technology with respect to Agile development which handles huge amount of data at a time. The Big data relies on 3V challenges namely, Volume, Variety and Velocity of data. It is generally known that the data coming from various data sources in various formats accumulate continuously together making traditional batch based model infeasible for real time data mining. This is the biggest challenge with the Big Data. As Velocity is one challenge in Big data, the crucial thing is to mine valuable and relevant data. To perform efficient data mining over such high speed data the Big data technology getting importance now a days. The Feature selection technique is used for data stream mining on the fly in Big data. Feature selection has been widely used to minimize the processing load in inducing the mining data model.

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