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In machine learning, hyperparameter optimization [1] or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process, which must be configured before the process starts.
One often uses a prior which comes from a parametric family of probability distributions – this is done partly for explicitness (so one can write down a distribution, and choose the form by varying the hyperparameter, rather than trying to produce an arbitrary function), and partly so that one can vary the hyperparameter, particularly in the method of conjugate priors, or for sensitivity ...
In machine learning, a hyperparameter is a parameter that can be set in order to define any configurable part of a model's learning process. Hyperparameters can be classified as either model hyperparameters (such as the topology and size of a neural network) or algorithm hyperparameters (such as the learning rate and the batch size of an optimizer).
{{google|1 pound in kilograms {{=}}}} 1 pound in kilograms = Use Template:= to add an = sign to trigger Google Calculator when necessary; that template cannot be substituted. {{google|1 pound in kilograms}} 1 pound in kilograms: Google may display Calculator results for some expressions even if they lack a trailing equals sign.
The |plainurl= parameter tells the template to output a URL (web address) only, rather than a linked book title and page number. Use |plainurl=yes when using this template in a |url= parameter of a citation template. |plain-url= works as an alias. In many cases when converting an existing Google Books URL, only one of the above should be used.
This template is a cut-down instance of the more general {{Google custom}} template. You may wish to make similar templates if you need to create repetitive links to other portions of Wikipedia that {{Google custom}} can search. This saves much typing compared to using {{Google custom}} for each link.
If the tokens were to choose the experts, then some experts might few tokens, while a few experts get so many tokens that it exceeds their maximum batch size, so they would have to ignore some of the tokens. Similarly, if the experts were to choose the tokens, then some tokens might not be picked by any expert. This is the "token drop" problem.
Google Docs is an online word processor and part of the free, web-based Google Docs Editors suite offered by Google. Google Docs is accessible via a web browser as a web-based application and is also available as a mobile app on Android and iOS and as a desktop application on Google's ChromeOS .