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AnomalyDetectorConfiguration

Used by
Source code in docs_src/capo_cloudwatch/types/anomaly_detector_configuration.py 
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class AnomalyDetectorConfiguration(TypedDict, closed=True):
    excluded_time_ranges: NotRequired[
        "capo_cloudwatch.types.anomaly_detector_excluded_time_ranges.AnomalyDetectorExcludedTimeRanges"
    ]
    """<p>An array of time ranges to exclude from use when the anomaly detection model is trained. Use this to make sure that events that could cause unusual values for the metric, such as deployments, aren't used when CloudWatch creates the model.</p>"""
    metric_timezone: NotRequired[
        "capo_cloudwatch.types.anomaly_detector_metric_timezone.AnomalyDetectorMetricTimezone"
    ]
    """<p>The time zone to use for the metric. This is useful to enable the model to automatically account for daylight savings time changes if the metric is sensitive to such time changes.</p> <p>To specify a time zone, use the name of the time zone as specified in the standard tz database. For more information, see <a href="https://en.wikipedia.org/wiki/Tz_database">tz database</a>.</p>"""

excluded_time_ranges instance-attribute 

excluded_time_ranges: NotRequired[AnomalyDetectorExcludedTimeRanges]

An array of time ranges to exclude from use when the anomaly detection model is trained. Use this to make sure that events that could cause unusual values for the metric, such as deployments, aren't used when CloudWatch creates the model.

metric_timezone instance-attribute 

metric_timezone: NotRequired[AnomalyDetectorMetricTimezone]

The time zone to use for the metric. This is useful to enable the model to automatically account for daylight savings time changes if the metric is sensitive to such time changes.

To specify a time zone, use the name of the time zone as specified in the standard tz database. For more information, see tz database.