Adding a custom algorithm to the Splunk Machine Learning Toolkit

Complete the following steps to add a custom algorithm to the Splunk Machine Learning Toolkit (MLTK):

1. Register the custom algorithm in the MLTK app.
2. Create a Python script file for the custom algorithm.
3. Write a Python algorithm class.
   1. The algorithm class must implement methods which are outlined in the BaseAlgo class in $SPLUNK_HOME/etc/apps/Splunk_ML_Toolkit/bin/base.py.

Coding knowledge, advanced Python experience, or development experience is an asset when adding custom algorithms.

Custom algorithm examples

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

• Correlation Matrix example
• Agglomerative Clustering example
• Support Vector Regressor example
• Savitzky-Golay Filter example