AlphaD3M: Machine Learning Pipeline Synthesis
Iddo Drori
Yamuna Krishnamurthy
Rémi Rampin
Raoni Lourenço
Jorge Piazentin Ono
Kyunghyun Cho
Claudio Silva
J. Freire

Abstract
We introduce AlphaD3M, an automatic machine learning (AutoML) system based on meta reinforcement learning using sequence models with self play. AlphaD3M is based on edit operations performed over machine learning pipeline primitives providing explainability. We compare AlphaD3M with state-of-the-art AutoML systems: Autosklearn, Autostacker, and TPOT, on OpenML datasets. AlphaD3M achieves competitive performance while being an order of magnitude faster, reducing computation time from hours to minutes, and is explainable by design.
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