Creating, sharing, and deleting models in the Machine Learning Toolkit
The Splunk Machine Learning Toolkit (MLTK) provides custom search commands for machine learning. These commands use model files to store machine learning algorithm results on a dataset. This model can then be applied to other datasets.
Models are Splunk platform knowledge objects with configurable sharing and permissions. Models store in the same way as lookups.
Under the Models tab of the MLTK navigation bar, access any models created using the
fit command on the Search tab. By default, user-level (private) models store here:
Model size is impacted by the data used and the chosen algorithm. Maximum model size is configurable and can be viewed within the MLTK Settings (
Settings/ Algo Name/ max_model_size_mb).
- To learn more about Lookups, see About Lookups in the Knowledge Manager Manual
- To learn more about how to manage model size and other MLTK settings, see Configure Algorithm Performance Costs
Creating and using models
By default, MLTK models created with the
fit command are created in the namespace of the user who ran the search. Models are created using the
fit command and applied to datasets using the
apply command. For more details, see:
- To learn more about the
applycommands, see Understanding the fit and apply commands
Sharing models from other Splunk apps
MLTK can access pre-trained models provided by other Splunk apps, provided the following settings are in place:
- The pre-trained model has its sharing level set to global using standard knowledge object access settings.
- The pre-trained model does not have the same name as a model that already exists in MLTK.
- To learn more about knowledge object access settings, see Knowledge object permissions
- To learn more about building custom Splunk apps, see the Develop apps and add-ons for Splunk Enterprise
You can also delete models through the Models page. Follow these steps to delete a model:
- Click Models on the MLTK navigation bar.
- On the Models page, select the model that needs deletion.
- Click Delete in the Actions column.
- In the Delete Model window, click Delete again to verify that you want to delete the model.
Cluster Numeric Events Experiment Assistant workflow
Model permissions in the Machine Learning Toolkit
This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 5.3.3, 5.4.0
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