The following outputs can be generated by the Isolation Forest tool. Depending on your configuration and analysis requirements, you can select one or more outputs from the Outputs section.
|
Ouptut |
Type |
Description |
|---|---|---|
|
Anomalies |
Condition |
Indicates whether an observation is considered anomalous based on the trained Isolation Forest model and anomaly detection settings. |
|
Anomaly Score |
Signal |
Measures how unusual an observation is compared to the training data. Higher scores indicate a greater likelihood that the observation is anomalous. |
|
Model input properties |
Scalar |
Provides information about the model inputs used during training. This output can be used for model validation and troubleshooting. |
|
Training window |
Condition |
Identifies the time range used to train the Isolation Forest model. This output can be used to verify the training period and compare it with scored data. |