Splunk IT Service Intelligence

Splunk Machine Learning Toolkit: Calibrating Density Function Algorithm

sc2019
New Member

In the anomaly detection process, density function algorithm outputs isOutlier field with values 0 (Normal) and 1 (Abnormal) for each data point depending on the KPI behavior and historical data:

  1. Is there anyway to calibrate the density function algorithm where the data point can show Normal, Warning and Critical zones based on the severity of the anomaly?
  2. How to output the probability densities of the data points and graph them like kernel distributions?
0 Karma
*NEW* Splunk Love Promo!
Snag a $25 Visa Gift Card for Giving Your Review!

It's another Splunk Love Special! For a limited time, you can review one of our select Splunk products through Gartner Peer Insights and receive a $25 Visa gift card!

Review:





Or Learn More in Our Blog >>