Kaspersky Machine Learning for Anomaly Detection

ML model templates

ML model templates are created on the basis of ML models previously added to Kaspersky MLAD or created using the model builder functionality. ML model templates preserve the algorithm structure, set of elements, and the state of the ML model used to create the template. The training state of the created ML model will match the training state of the source ML model when the template was created.

Using templates, you can add ML models of the same type to Kaspersky MLAD. These models will analyze data received from equipment of the same type with a similar set of tags. When creating an ML model from a template, you can configure the use of other tags in the ML model by specifying tag IDs that differ from the ones in the source ML model.