BriefGPT.xyz
Aug, 2021
调参还是不调参?一种推荐重要超参数的方法
To tune or not to tune? An Approach for Recommending Important Hyperparameters
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Mohamadjavad Bahmani, Radwa El Shawi, Nshan Potikyan, Sherif Sakr
TL;DR
本文探讨机器学习模型性能和超参数之间的关系,通过实验结果发现了趋势和启示,并得出使用梯度提升和Adaboost分类器是最佳选择的结论。
Abstract
Novel technologies in
automated machine learning
ease the complexity of algorithm selection and
hyperparameter optimization
. Hyperparameters are important for
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