Package software.amazon.awssdk.services.sagemaker.model

Class TimeSeriesForecastingJobConfig

    • Method Detail

      • featureSpecificationS3Uri

        public final String featureSpecificationS3Uri()

        A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig . If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig.

        You can input FeatureAttributeNames (optional) in JSON format as shown below:

        { "FeatureAttributeNames":["col1", "col2", ...] }.

        You can also specify the data type of the feature (optional) in the format shown below:

        { "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }

        Autopilot supports the following data types: numeric, categorical, text, and datetime.

        These column keys must not include any column set in TimeSeriesConfig.

        Returns:
        A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig.

        You can input FeatureAttributeNames (optional) in JSON format as shown below:

        { "FeatureAttributeNames":["col1", "col2", ...] }.

        You can also specify the data type of the feature (optional) in the format shown below:

        { "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }

        Autopilot supports the following data types: numeric, categorical, text, and datetime.

        These column keys must not include any column set in TimeSeriesConfig.

      • completionCriteria

        public final AutoMLJobCompletionCriteria completionCriteria()
        Returns the value of the CompletionCriteria property for this object.
        Returns:
        The value of the CompletionCriteria property for this object.

      • forecastFrequency

        public final String forecastFrequency()

        The frequency of predictions in a forecast.

        Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D indicates every day and 15min indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H instead of 60min.

        The valid values for each frequency are the following:

        • Minute - 1-59

        • Hour - 1-23

        • Day - 1-6

        • Week - 1-4

        • Month - 1-11

        • Year - 1

        Returns:
        The frequency of predictions in a forecast.

        Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D indicates every day and 15min indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H instead of 60min.

        The valid values for each frequency are the following:

        • Minute - 1-59

        • Hour - 1-23

        • Day - 1-6

        • Week - 1-4

        • Month - 1-11

        • Year - 1

      • forecastHorizon

        public final Integer forecastHorizon()

        The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.

        Returns:
        The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.

      • hasForecastQuantiles

        public final boolean hasForecastQuantiles()
        For responses, this returns true if the service returned a value for the ForecastQuantiles property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

      • forecastQuantiles

        public final List<String> forecastQuantiles()

        The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.

        Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

        This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasForecastQuantiles() method.

        Returns:
        The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.

      • transformations

        public final TimeSeriesTransformations transformations()

        The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.

        Returns:
        The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.

      • timeSeriesConfig

        public final TimeSeriesConfig timeSeriesConfig()

        The collection of components that defines the time-series.

        Returns:
        The collection of components that defines the time-series.

      • hasHolidayConfig

        public final boolean hasHolidayConfig()
        For responses, this returns true if the service returned a value for the HolidayConfig property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

      • holidayConfig

        public final List<HolidayConfigAttributes> holidayConfig()

        The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.

        Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

        This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasHolidayConfig() method.

        Returns:
        The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.

      • hashCode

        public final int hashCode()
        Overrides:
        hashCode in class Object

      • equals

        public final boolean equals​(Object obj)
        Overrides:
        equals in class Object

      • toString

        public final String toString()
        Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
        Overrides:
        toString in class Object

      • getValueForField

        public final <T> Optional<T> getValueForField​(String fieldName,
                                              Class<T> clazz)