Automated Machine Learning using Evolutionary Algorithms

Abstract

As the global data quantity already follows an exponential trend, machine learning has become present in every application, creating a great demand for general knowhow, be it data scientists or computer scientists with related knowledge. Currently, the demand for work to be done surpasses the offer of such professionals, thus automatic solutions have to be found. The classical machine learning process involves data engineering, model selection, and hyperparameter tuning for the chosen model. Due to the highly repetitive nature of trial and error of these tasks, automation can play a big role in optimizing time spent on them. Automated Machine Learning comes to help the process by adding different optimization techniques that help data scientists be more productive and achieve similar or better results in a shorter time. This paper provides a novel approach to Automated Machine Learning using Evolutionary Algorithms and proves its performance by presenting top results in benchmark tests.