Splunk® Machine Learning Toolkit

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Machine Learning Toolkit version dependencies

The Machine Learning Toolkit (MLTK) releases updates on a regular schedule. Keep your instance of the MLTK and affiliated add-ons up-to-date to access the latest features.

The MLTK requires installation of the Python for Scientific Computing (PSC) add-on. Refer to the following table to ensure you are running the correct version of the MLTK, PSC, Python, and Splunk Enterprise.

If you have any custom algorithms that rely on the PSC libraries, upgrading the PSC library add-on will impact those algorithms. You must re-train any models (re-run the search that used the fit command) using those algorithms after you upgrade the PSC add-on.

MLTK version PSC add-on version Python version Splunk Enterprise version Notes
5.2.0 2.0.0 or 2.0.1 3 8.0 required This version of the MLTK is only available with Splunk Enterprise version 8.0.
5.1.0 2.0.0 3 8.0 required This version of the MLTK is only available with Splunk Enterprise version 8.0.
5.0.0 2.0.0 3 8.0 required This version of the MLTK is only available with Splunk Enterprise version 8.0. Users upgrading to this version must retrain models created in earlier versions of the MLTK. The file extension for models has changed from .csv to .mlmodel.
4.5.0 1.4 2.x 7.x This version includes all the features of version 5.0.0 barring the support of the random_state parameter of the DensityFunction anomaly detection algorithm. Models created in earlier versions of the MLTK maintain compatibility and do not require retraining.
4.4.2 1.4 or 1.3 2.x 7.x No new features from version 4.4.1. PSC version 1.4 recommended.
4.4.1 1.4 or 1.3 2.x 7.x PSC version 1.4 recommended.
4.4.0 1.4 or 1.3 2.x 7.x PSC version 1.4 recommended.

Version 2.0.1 of PSC is limited to a minor library upgrade from version 2.0.0 with no differences in functionality to version 2.0.0.

Last modified on 23 July, 2020
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This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 5.2.0


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