Whether it's predicting failures in your infrastructure or detecting anomalies in a fleet of vehicles, Splunk Search Processing Language gives you the power of machine learning on any machine data. For example, the anomaly detection command is used to find anomalous behavior within your data. Here, it's filtered down our results to specific anomalies.

Using the Fit command and an associated algorithm, you can fit a model to predict the value of a numerical or categorical field, then apply the model to an incoming data set.

To make this process even easier, Splunk created the machine learning tool kit, where you can fit and apply your models through a guided interface, then test and refine the accuracy of your models, additionally, analyze the actual versus predicted values, and view the residuals.

Download the machine learning tool kit on Splunk Base to learn about examples of machine learning use cases and how the power of Splunk's SPL can harness your machine data. Learn more about Splunk Search Processing Language at docs.splunk.com.


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