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

Interface TimeSeriesForecastingJobConfig.Builder

    • Method Detail

      • featureSpecificationS3Uri

        TimeSeriesForecastingJobConfig.Builder featureSpecificationS3Uri​(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.

        Parameters:
        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:
        Returns a reference to this object so that method calls can be chained together.

      • completionCriteria

        TimeSeriesForecastingJobConfig.Builder completionCriteria​(AutoMLJobCompletionCriteria completionCriteria)
        Sets the value of the CompletionCriteria property for this object.
        Parameters:
        completionCriteria - The new value for the CompletionCriteria property for this object.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • forecastFrequency

        TimeSeriesForecastingJobConfig.Builder forecastFrequency​(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

        Parameters:
        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:
        Returns a reference to this object so that method calls can be chained together.

      • forecastHorizon

        TimeSeriesForecastingJobConfig.Builder forecastHorizon​(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.

        Parameters:
        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:
        Returns a reference to this object so that method calls can be chained together.

      • forecastQuantiles

        TimeSeriesForecastingJobConfig.Builder forecastQuantiles​(Collection<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.

        Parameters:
        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.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • forecastQuantiles

        TimeSeriesForecastingJobConfig.Builder forecastQuantiles​(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.

        Parameters:
        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.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • transformations

        TimeSeriesForecastingJobConfig.Builder transformations​(TimeSeriesTransformations transformations)

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

        Parameters:
        transformations - The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • timeSeriesConfig

        TimeSeriesForecastingJobConfig.Builder timeSeriesConfig​(TimeSeriesConfig timeSeriesConfig)

        The collection of components that defines the time-series.

        Parameters:
        timeSeriesConfig - The collection of components that defines the time-series.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • holidayConfig

        TimeSeriesForecastingJobConfig.Builder holidayConfig​(Collection<HolidayConfigAttributes> holidayConfig)

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

        Parameters:
        holidayConfig - The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
        Returns:
        Returns a reference to this object so that method calls can be chained together.

      • holidayConfig

        TimeSeriesForecastingJobConfig.Builder holidayConfig​(HolidayConfigAttributes... holidayConfig)

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

        Parameters:
        holidayConfig - The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
        Returns:
        Returns a reference to this object so that method calls can be chained together.