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Naive automated machine learning

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Bibliographic Details
Main Authors: Felix, Mohr, Marcel, Wever
Format: Book
Language:English
Published: Springer 2023
Subjects:
automated machine learning
AutoML
Online Access:https://link.springer.com/article/10.1007/s10994-022-06200-0
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7383
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spelling oai:localhost:PNK-73832023-03-31T07:09:17Z Naive automated machine learning Felix, Mohr Marcel, Wever automated machine learning AutoML CC BY An essential task of automated machine learning (AutoML ) is the problem of automatically finding the pipeline with the best generalization performance on a given dataset. This problem has been addressed with sophisticated black-box optimization techniques such as Bayesian optimization, grammar-based genetic algorithms, and tree search algorithms. Most of the current approaches are motivated by the assumption that optimizing the components of a pipeline in isolation may yield sub-optimal results. We present Naive AutoML , an approach that precisely realizes such an in-isolation optimization of the different components of a pre-defined pipeline scheme. 2023-03-31T07:09:17Z 2023-03-31T07:09:17Z 2023 Book https://link.springer.com/article/10.1007/s10994-022-06200-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7383 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic automated machine learning
AutoML
spellingShingle automated machine learning
AutoML
Felix, Mohr
Marcel, Wever
Naive automated machine learning
description CC BY
format Book
author Felix, Mohr
Marcel, Wever
author_facet Felix, Mohr
Marcel, Wever
author_sort Felix, Mohr
title Naive automated machine learning
title_short Naive automated machine learning
title_full Naive automated machine learning
title_fullStr Naive automated machine learning
title_full_unstemmed Naive automated machine learning
title_sort naive automated machine learning
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s10994-022-06200-0
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7383
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score 8.891787

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