A Gaussian Approach to the Detection of Anomalous Behavior in Server Computers

Author(s): Navoneel Chakrabarty

Originally published on Towards AI.

Let’s detect the anomaly…

Anomaly Detection is a different variant of Machine Learning Problems that falls under Semi-Supervised Learning. It is Semi-Supervised because, in Anomaly Detection (also popularly known as Outlier Detection), models often involve parameters that are fit using the Validation Set labels whereas the training procedure does not involve Training Set labels. Also, the Test Set labels are used for evaluating model performance metrics like Accuracy, Precision, Recall, F1-Score and AUROC (Area Under the ROC Curve).

One such common approach for Anomaly Detection is the Gaussian Distribution. In this approach, all the features are modeled on a Gaussian Distribution and given a new… Read the full blog for free on Medium.

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Published via Towards AI