AlphaD3M: Machine Learning Pipeline Synthesis

Autor:	Drori, Iddo, Krishnamurthy, Yamuna, Rampin, Remi, Lourenco, Raoni de Paula, Ono, Jorge Piazentin, Cho, Kyunghyun, Silva, Claudio, Freire, Juliana
Rok vydání:	2021
Předmět:	Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: ICML 2018 AutoML Workshop
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2111.02508 Zobrazit plný text záznamu View this record from Arxiv