Thông tin tài liệu
Nhan đề : | Naive automated machine learning |
Tác giả : | Felix, Mohr Marcel, Wever |
Năm xuất bản : | 2023 |
Nhà xuất bản : | Springer |
Tóm tắt : | 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. |
Mô tả: | CC BY |
URI: | https://link.springer.com/article/10.1007/s10994-022-06200-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7383 |
Bộ sưu tập | OER - Công nghệ thông tin |
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