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I used anomaly detection from AutoML on my dataset to create a model. How to interpret metrics for isolation forest? e.g. what do the values for silhouette = .437 and inertia = 0 signify?
I would love an answer to this as well.
Googling how to generally interpret anomaly scores using isolation forest seems to indicate that values close to one are anomalous, but using the dataiku isolation forest for anomaly detection seems to return anomalies with values closer to zero. How does dataiku's isolation forest method differ from the more general approach?