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.

Running process and method calling convention

There are a few parts of the logic that you need to be familiar with.

Fit command

In the fit command, when partial_fit=f (default), first the algorithm's fit method is called. If it returns a DataFrame, we return that to the search. If it doesn't, we will call apply later, then return whatever DataFrame apply gives us.

Fit diagram.png

Fit command partial_fit=t

In the fitcommand, when partial_fit=t, the algorithm's partial_fit method is called on each chunk of 50,000 events. Then apply is called on those events. We continue this process until we run out of data.

Partial fit.png

Apply Command

In the apply command, things are much simpler. We reconstruct the python object by using its codec, then call apply on the events, chunk by chunk.

Apply.png

Summary Command

In the summary command, things are similar to apply. We reconstruct the python object by using its codec, then call summary.

Summarycommand.png

Last modified on 24 May, 2017
Write an algorithm class   Correlation Matrix

This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 2.2.0, 2.2.1

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