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


Was this topic useful?







You must be logged into splunk.com in order to post comments. Log in now.

Please try to keep this discussion focused on the content covered in this documentation topic. If you have a more general question about Splunk functionality or are experiencing a difficulty with Splunk, consider posting a question to Splunkbase Answers.

0 out of 1000 Characters