Automated Machine Learning: From Principles to Practices

arXiv:1810.13306v5 Announce Type: replace-cross
Abstract: Machine learning (ML) methods have been developing rapidly, but configuring and selecting proper methods to achieve a desired performance is increasingly difficult and tedious. To address this challenge, automated machine learning (AutoML) has emerged, which aims to generate satisfactory ML configurations for given tasks in a data-driven way. In this paper, we provide a comprehensive survey on this topic. We begin with the formal definition of AutoML and then introduce its principles, including the bi-level …

abstract arxiv automated automated machine learning automl challenge cs.ai cs.lg data data-driven generate machine machine learning performance practices stat.ml tasks type