Why don't you use Evolutionary Algorithms in Big Data?

5th International Workshop on Mathematical Models and their Applications 2016

Stanovov, Vladimir^1 ; Brester, Christina^1 ; Kolehmainen, Mikko^2 ; Semenkina, Olga^1

Siberian State Aerospace University, Krasnoyarsky Rabochy Av., 31, Krasnoyarsk

660037, Russia^1

University of Eastern Finland, Yliopistonranta 1 E, Kuopio

70211, Finland^2

关键词: Global optimization problems;    High scalabilities;    Instance selection;    Reduction problem;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/173/1/012020/pdf
DOI  :  10.1088/1757-899X/173/1/012020

来源: IOP

【 摘 要 】

In this paper we raise the question of using evolutionary algorithms in the area of Big Data processing. We show that evolutionary algorithms provide evident advantages due to their high scalability and flexibility, their ability to solve global optimization problems and optimize several criteria at the same time for feature selection, instance selection and other data reduction problems. In particular, we consider the usage of evolutionary algorithms with all kinds of machine learning tools, such as neural networks and fuzzy systems. All our examples prove that Evolutionary Machine Learning is becoming more and more important in data analysis and we expect to see the further development of this field especially in respect to Big Data.