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In the last few years, Automated Machine Learning (AutoML) has gained muchattention. With that said, the question arises whether AutoML can outperformresults achieved by human data scientists. This paper compares four AutoMLframeworks on 12 different popular datasets from OpenML; six of them supervisedclassification tasks and the other six supervised regression ones.Additionally, we consider a real-life dataset from one of our recent projects.The results show that the automated frameworks perform better or equal than themachine learning community in 7 out of 12 OpenML tasks.

Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark