Multi Objective Optimization Based Feature Selection Algorithms for Big Data Analytics: A Review

Dimension reduction or feature selection is thought to be the backbone of big data applications in order improve performance. Many scholars have shifted their attention recent years science and analysis for real-time using integration. It takes a long time humans interact with data. As result, while handling high workload distributed system, it necessary make elastic scalable. In this study, survey alternative optimizing techniques are presented, as well an analytical result limits. This study contributes development method improving efficiency complicated sets.