tw.anomaly_detection.detect

Detect anomalies using a previously built model. Submits a detection job, polls until it completes, and returns the detection results together with job metadata.

dataset : pandas.DataFrame

Time-series data on which anomaly detection is performed.

model: dict

A trained anomaly-detection model (as returned by method: “build_model”).

dict

A dictionary with keys:

"id" – job identifier (str).

"results" – detection results as a :class:`pandas.DataFrame`.

"status" – final job status response (dict).

anomaly_detection_detect_response = tw.anomaly_detection.detect(
    model = anomaly_detection_build_model_model,
    dataset = dataset
)

anomaly_detection_detect_id = anomaly_detection_detect_response['id']
anomaly_detection_detect_results = anomaly_detection_detect_response['results']
anomaly_detection_detect_status = anomaly_detection_detect_response['status']