FLAML: A Fast and Lightweight AutoML Library
We study the problem of using low computational cost to automate the choices of learners and hyperparameters for an ad-hoc training dataset and error metric, by conducting trials of different configurations on the given training data. We investigate the joint impact of multiple factors on both trial...
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Main Authors | , , , |
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Format | Journal Article |
Language | English |
Published |
12.11.2019
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Subjects | |
Online Access | Get full text |
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