tw.endpoints.anomaly_detection.rca

tw.endpoints.anomaly_detection.rca(configuration=dict,dataset=pandas.DataFrame,model=dict)

Submit a root-cause analysis job.
POST ``/anomaly-detection/rca``

Parameters

configuration : dict

RCA configuration payload.

dataset : pandas.DataFrame

Data associated with the anomalies to analyse.

model: dict

A trained anomaly-detection model.

Returns

dict

API response containing at least ``"id"`` (the new job identifier).

Example Configuration

CODE

anomaly_detection_rca_configuration = {
    "model_indexes": [
        1
    ]
}

Example Usage

CODE

anomaly_detection_rca_response = tw.endpoints.anomaly_detection.rca(
    configuration = anomaly_detection_rca_configuration,
    dataset = dataset,
    model = model
)

Example Output

CODE

anomaly_detection_rca_id = anomaly_detection_rca_response['id']