A parameter that is not strictly for the statistical model (or data generating process), but a parameter for the statistical method. It could be a parameter for: a family of prior distributions, smoothing, a penalty in regularization methods, or an optimization algorithm.
Questions tagged [hyperparameter]
650 questions
4
votes
0 answers
Hyperopt with TPE strategy always sampling the same points
I want to do a convergence study of Ridge regression with increasing training size. For this I train the Ridge regressor using hyperopt for different training sizes [10, 20, 40, 80]. As far as I understand, the TPE strategy adapts to the…
Michael
- 233
2
votes
1 answer
Tuning of Hyperparameter
Are there any advanced packages that allows automated tuning of hyperparameters for neural network and traditional machine learning algorithms like XGBoost, random forest (using method like Bayesian, random search etc. that could allow faster…
william007
- 1,087
2
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0 answers
Why is there a perceived difference between a Bayesian Hyperparameter and a Machine Learning Hyperparameter?
There are two seperate Wikipedia articles for the term Hyperparameter. One for Bayesian statistics and another for machine learning methods.
Why is this so? BOTH of these definitions imply that hyperparameters influence other parameters. I notice…
user46925
0
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0 answers
How much improvement in performance should one expect from hyperparameter tuning?
Is there a general conclusion on what one should expect from hyperparameter tuning? For instance, is it always the case that hyperparameter can only increase the performance from OK to good (say 0.75 r-score to 0.90) or is it possible to see a jump…
xshang
- 1