Splunk Machine Learning Toolkit version dependencies

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

• For a list view of features included by release version, see What's new in the Splunk Machine Learning Toolkit.
• For installation information including links to Splunkbase for required add-ons, see Upgrade the Splunk Machine Learning Toolkit.

About the PSC add-on

MLTK requires installation of the Python for Scientific Computing (PSC) add-on. Version 4.2.0 of PSC includes some new libraries and packages. See, MLTK version 5.4.1 features and improvements.

Versions 4.2.0, 4.1.2, 4.1.0, and 3.1.0 of the Python for Scientific Computing (PSC) add-on include the ONNX library. Use one of these versions to bring pre-trained ONNX models into MLTK. This ONNX model feature is only available with MLTK version 5.4.0 or higher. See, Upload and inference pre-trained ONNX models in MLTK.

If you have any custom algorithms that rely on the PSC libraries, upgrading the PSC 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.

Version matrix

See the following table for the compatible combinations of MLTK, the PSC add-on, Python, and the Splunk platform:

MLTK version	PSC add-on version	Python version	Splunk platform version	Notes
5.4.1	4.1.2, or 4.2.0	3	Splunk Enterprise 9.2.x or Splunk Cloud Platform	PSC version 4.2.0 is a minor release that offers additional packages.
	3.1.0, 4.1.0, 4.1.2, or 4.2.0	3	Splunk Enterprise 8.1.x, 8.2.x, 9.0.0, 9.0.1, 9.0.5, or 9.1.0 or Splunk Cloud Platform	PSC version 4.2.0 is a minor release that offers additional packages.
5.4.0	4.1.2	3	Splunk Enterprise 9.2.x or Splunk Cloud Platform	Version 3.1.0, 4.1.0, or 4.1.2 of the PSC add-on is required to use the upload ONNX models feature.
	3.1.0, 4.1.0, or 4.1.2	3	Splunk Enterprise 8.2.x, 9.0.0, 9.0.1, 9.0.5, or 9.1.0 or Splunk Cloud Platform	Version 3.1.0, 4.1.0, or 4.1.2 of the PSC add-on is required to use the upload ONNX models feature.
5.3.3	3.0.2, 3.1.0, 4.0.0, 4.1.0, or 4.1.2	3	Splunk Enterprise 8.1.x, 8.2.x, or 9.0.0 or Splunk Cloud Platform	Version 4.0.0 of the PSC add-on requires additional installation steps. See, Install version 4.0.0 of the PSC add-on. Deprecated support of Internet Explorer.
5.3.1	3.0.0, 3.0.1, or 3.0.2	3	Splunk Enterprise 8.0.x, 8.1.x, 8.2.x, or 9.0.0 or Splunk Cloud Platform	Version 3.0.2 of the PSC add-on is limited to bug fixes.
5.3.0	3.0.0, 3.0.1, or 3.0.2	3	Splunk Enterprise 8.0.x, 8.1.x, 8.2.x, or 9.0.0 or Splunk Cloud Platform	This version of MLTK requires version 3.0.0, 3.0.1, or 3.0.2 of the PSC add-on. Users upgrading to this version must retrain models created in earlier versions of MLTK.
5.2.2	2.0.0, 2.0.1, or 2.0.2	3	Splunk Enterprise 8.0.x, 8.1.x, or 8.2.0 or Splunk Cloud Platform	This version of MLTK is limited to a minor enhancement.
5.2.1	2.0.0, 2.0.1, or 2.0.2	3	Splunk Enterprise 8.0.x, 8.1.x, or 8.2.0 or Splunk Cloud Platform	This version of MLTK is limited to a minor enhancement.
5.2.0	2.0.0, 2.0.1, or 2.0.2	3	Splunk Enterprise 8.0.x, 8.1.x, or 8.2.0 or Splunk Cloud Platform	This version of MLTK is available with Splunk Enterprise version 8.0.x, 8.1.x, or 8.2.0.
5.1.0	2.0.0, 2.0.1, or 2.0.2	3	Splunk Enterprise 8.0.x or 8.1.x or Splunk Cloud Platform	This version of MLTK is available with Splunk Enterprise version 8.0.x or 8.1.x.
5.0.0	2.0.0, 2.0.1, or 2.0.2	3	Splunk Enterprise 8.0.x or 8.1.x or Splunk Cloud Platform	This version of MLTK is only available with Splunk Enterprise version 8.0.x or 8.1.x. Users upgrading to this version must retrain models created in earlier versions of MLTK. The file extension for models has changed from .csv to .mlmodel.
4.5.0	1.4	2.x	Splunk Enterprise 7.x or Splunk Cloud Platform	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 MLTK maintain compatibility and do not require retraining.