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Required Feature Group Types

To train a model under this use case, you will need to create feature groups of the following type(s):

Feature Group Type	API Configuration Name	Required	Description
Event/Data log	EVENT_LOG	True	This dataset contains the events you are trying to detect anomalies for, and is what the model is fitted on.
Known Anomalies	TEST_LOG	False	This dataset contains some known anomalies that we will evaluate the fitted model on as a test set.

Note: Once you upload the datasets under each Feature Group Type that comply with their respective required schemas, you will need to create Machine learning (ML) features that would be used to train your ML model(s). We use the term, "Feature Group" for a group of ML features (dataset columns) under a specific Feature Group Type. Our system support extensible schemas that enables you to provide any number of additional columns/features that you think are relevant to that Feature Group Type.

Feature Group: Event/Data log

This dataset contains the events you are trying to detect anomalies for, and is what the model is fitted on.

Feature Mapping	Feature Type	Required	Description
[ATTRIBUTE RELEVANT TO EVENT LOGS]		Y	Any attribute relevant to the event log that we will use in detecting anomalies.

Feature Group: Known Anomalies

This dataset contains some known anomalies that we will evaluate the fitted model on as a test set.

Feature Mapping	Feature Type	Required	Description
[ATTRIBUTE RELEVANT TO EVENT LOGS]		Y	Any attribute relevant to the event log that we will use in detecting anomalies.