Splunk® Machine Learning Toolkit

ML-SPL API Guide

This documentation does not apply to the most recent version of Splunk® Machine Learning Toolkit. For documentation on the most recent version, go to the latest release.

Add a custom algorithm to the Machine Learning Toolkit overview

To add a custom algorithm to the Splunk Machine Learning Toolkit, you must register the algorithm in the MLTK app, create a Python script file for the algorithm, and write a Python algorithm class. The algorithm class must implement certain methods which are outlined in the BaseAlgo class in $SPLUNK_HOME/etc/apps/Splunk_ML_Toolkit/bin/base.py.

For information about the algorithms packaged with the Splunk Machine Learning Toolkit, see Algorithms in the Machine Learning Toolkit in the User Guide.

Coding is required to add a custom algorithm to the Splunk Machine Learning Toolkit. Development experience is an asset.

Custom algorithm examples

You can view end-to-end examples for the following custom algorithms:

Last modified on 25 January, 2024
About the ML-SPL API   Register an algorithm in the Machine Learning Toolkit

This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 4.4.0, 4.4.1, 4.4.2, 4.5.0

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