Classification techniques for big data using bio inspired and hybrid models

Abstract

In this bigdata era, it is important to learn from bigdata in many areas, newlineincluding machine learning, pattern recognition, information retrieval, and newlineimage processing. Big data analytics helps organizations harness the data and newlineuse it to identify new opportunities. Businesses that use big data with newlineadvanced analytics gain value in many ways. newlineThe key challenge in bigdata analysis is to perform analytical functions newlinesuch as random and noise-free data diversification, pre-processing, newlineintegration, and transformation. A lot of data spill from an assortment of newlinesources, including information administrations, machine-produced newlineinformation, and virtual entertainment information. This different information newlineshould be gathered and put away so significant data can be handled and newlineinvestigated proficiently. The challenge is to develop algorithmic solutions newlinethat integrate different data from different sources using integrated search, newlinequery, and analysis. Traditional analysis algorithms, such as data and data newlineprocessing tools, are insufficient to meet the challenges of modern data newlineanalysis. newline newline