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- W3149109741 abstract "Automated Machine Learning (Auto-ML) is a growing field where several techniques are being developed to address the question of how to automate the process of defining machine learning pipelines, using diverse types of approaches and with relative success, but still, being far from solved. Among these still unsolved questions, the computational cost is one of the major issues. In this context, evaluating a model takes a lot of time and resources, and yet that is still a step that has not received much attention in the Auto-ML literature." @default.
- W3149109741 created "2021-04-13" @default.
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- W3149109741 date "2021-01-01" @default.
- W3149109741 modified "2023-09-24" @default.
- W3149109741 title "Evaluating Models with Dynamic Sampling Holdout" @default.
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- W3149109741 doi "https://doi.org/10.1007/978-3-030-72699-7_46" @default.
- W3149109741 hasPublicationYear "2021" @default.
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