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Recently, Automated Machine Learning (AutoML) has registered increasingsuccess with respect to tabular data. However, the question arises whetherAutoML can also be applied effectively to text classification tasks. This workcompares four AutoML tools on 13 different popular datasets, including Kagglecompetitions, and opposes human performance. The results show that the AutoMLtools perform better than the machine learning community in 4 out of 13 tasksand that two stand out.

Leveraging Automated Machine Learning for Text Classification: Evaluation of AutoML Tools and Comparison with Human Performance