Predictive classifier techniques for big data application in cloud environment

Abstract

Big data involves a massive volume of data that are so large and it is difficult to process using traditional database and software techniques In the use of big data applications a technical barrier is encountered when moving the data across various locations which is very expensive and it requires large main memory for holding data for computing Big data includes transaction and interaction of datasets based on the size and complexity that exceed the regular technical capability in capturing organizing and processing data in cloud environment It has real time data intensive processing that runs on high performance clusters Big data applications are handled for sharing the structured and unstructured information by collecting the data effectively to achieve faster response and reduced classification time newlineExisting researches focus on data mining with big data using heterogeneous autonomous complex evolving theorem that improves the security and privacy in cloud environment Another prototype method called Flex Analytics is designed to increase the bandwidth of data transmission Centralized control unit is used in data applications to identify the attacks and malfunctions in enormous amount of data. Cloud computing is a parallel distributed computing system that has become a frequently used computing application for big data analytics However both the methods do not address the issues related to space and time complexity newlineA distributed framework named as MapReduce for prototype reduction handles the classification performance MapReduce technique splits the data based on the big data applications. Its prototype avoids the preprocessed dataset that results in reduced processing time newline newline