hyperparameter
1
8.8
- noun
- /ˌhaɪpərpəˈramɪtər/
- Specialized
- The effectiveness of the algorithm often depends on the tuning of its hyperparameters.
Examples
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If you're working on a difficult problem and can't directly estimate the unexplained group-level information, then I'd recommend setting these hyperparameters based on what prior information you have, recognizing the possible dependence of your conclusions on these assumptions.
Blog text (6) -
Selecting appropriate hyperparameters can significantly enhance the performance of your machine learning model.
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These hyperparameters were chosen from wide and substantial sets of ranges.
Academic text (2018) -
The last part of this Bayesian method is to choose the hyperparameters a and b for the Be(a, b) distribution.
Academic text (2010) -
Again, the hyperparameter choices are essential to the endpoints of the confidence interval, particularly for n = 10 and where Y1 or Y2 are near 0 or n.
Academic text (2010) -
Table 5 shows the best hyperparameters for the tested models based on the validation sets in the CV5 experiment over all unique trajectories of all users together.
Academic text (2018) -
To optimize the model, it is crucial to adjust the hyperparameters based on the dataset's characteristics.
Synonyms
143
6.7
A factor that affects how a system or process works
Surface Forms
Morphology
Etymology
The word hyperparameter combines hyper- meaning 'over' or 'above', as in hyperactive, and parameter, a common word for a 'setting' used in models. So a hyperparameter is an 'above' setting that controls how a model is trained and affects its performance.