Anomaly detection with term aggregations

I’ve been doing some research on the Anomaly Detection plugin and comparing the results with a separate analysis performed in Python. The use-case included searching for security anomalies, such as the number of 401 and 403 statuses per IP/user. For aggregating feature data I used single-value aggregations such as value_count and cardinality. The results are quite satisfactory.

I’ve got a couple more use cases I would like to try out but I’m not sure if Anomaly Detection supports such functionality. For example, I would like to perform term aggregations on features and search for anomalies within the count of terms. Specifically, I would like to provide the following input to the model:

[ { "country": "US", "doc_count": 1000 }, { "country": "CA", "doc_count": 700, }, { "country": "FR", "doc_count": 2, } ]

The expected behavior here would be showing an anomaly for France which is not a country visitors usually come from.

Is this functionality currently available with the plugin? If not, is it planned for implementation?