hyperparameter
Summary
Records a hyperparameter used to build the AI model contained in the AI package.
Description
Records a hyperparameter value.
Hyperparameters are settings defined before the training process that control the learning algorithm's behavior. They differ from model parameters, which are learned from the data during training. Developers typically set hyperparameters manually or through a process of hyperparameter tuning (also known as trial and error).
Examples of hyperparameters include learning rate, batch size, and the number of layers in a neural network.
Metadata
https://spdx.org/rdf/3.0.1/terms/AI/hyperparameter
| Name | hyperparameter |
| Nature | ObjectProperty |
| Range | /Core/DictionaryEntry |