AlphaD3M: Machine Learning Pipeline Synthesis

Iddo Drori; Yamuna Krishnamurthy; Remi Rampin; Raoni de Paula Lourenco; Jorge Piazentin Ono; Kyunghyun Cho; Claudio Silva; Juliana Freire

arXiv · 2111.02508

AlphaD3M: Machine Learning Pipeline Synthesis

Iddo Drori·Yamuna Krishnamurthy·Remi Rampin·Raoni de Paula Lourenco·Jorge Piazentin Ono·Kyunghyun Cho·Claudio Silva·Juliana Freire

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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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Iddo Drori, Yamuna Krishnamurthy, Remi Rampin, Raoni de Paula Lourenco, Jorge Piazentin Ono, Kyunghyun Cho, Claudio Silva, Juliana Freire. 2021-11-03. AlphaD3M: Machine Learning Pipeline Synthesis. https://arxiv.org/abs/2111.02508

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