forecasting

type Client struct {
	// contains filtered or unexported fields
}

type CreateForecastingExperimentRequest struct {
	// The fully qualified path of a Unity Catalog table, formatted as
	// catalog_name.schema_name.table_name, used as training data for the
	// forecasting model.
	TrainDataPath *string
	// The column in the input training table used as the prediction target for
	// model training. The values in this column are used as the ground truth for
	// model training.
	TargetColumn *string
	// The column in the input training table that represents each row's timestamp.
	TimeColumn *string
	// The time interval between consecutive rows in the time series data. Possible
	// values include: '1 second', '1 minute', '5 minutes', '10 minutes', '15
	// minutes', '30 minutes', 'Hourly', 'Daily', 'Weekly', 'Monthly', 'Quarterly',
	// 'Yearly'.
	ForecastGranularity *string
	// The number of time steps into the future to make predictions, calculated as a
	// multiple of forecast_granularity. This value represents how far ahead the
	// model should forecast.
	ForecastHorizon *int64
	// The evaluation metric used to optimize the forecasting model.
	PrimaryMetric *string
	// List of frameworks to include for model tuning. Possible values are
	// 'Prophet', 'ARIMA', 'DeepAR'. An empty list includes all supported
	// frameworks.
	TrainingFrameworks []string
	// The path in the workspace to store the created experiment.
	ExperimentPath *string
	// The maximum duration for the experiment in minutes. The experiment stops
	// automatically if it exceeds this limit.
	MaxRuntime *int64
	// // The column in the training table used for custom data splits. Values must
	// be 'train', 'validate', or 'test'.
	SplitColumn *string
	// The column in the training table used to customize weights for each time
	// series.
	CustomWeightsColumn *string
	// The fully qualified path of a Unity Catalog model, formatted as
	// catalog_name.schema_name.model_name, used to store the best model.
	RegisterTo *string
	// The region code(s) to automatically add holiday features. Currently supports
	// only one region.
	HolidayRegions []string
	// The column in the training table used to group the dataset for predicting
	// individual time series.
	TimeseriesIdentifierColumns []string
	// The fully qualified path of a Unity Catalog table, formatted as
	// catalog_name.schema_name.table_name, used to store predictions.
	PredictionDataPath *string
	// Specifies the list of feature columns to include in model training. These
	// columns must exist in the training data and be of type string, numerical, or
	// boolean. If not specified, no additional features will be included. Note:
	// Certain columns are automatically handled: - Automatically excluded:
	// split_column, target_column, custom_weights_column. - Automatically included:
	// time_column.
	IncludeFeatures []string
	// The fully qualified path of a Unity Catalog table, formatted as
	// catalog_name.schema_name.table_name, used to store future feature data for
	// predictions.
	FutureFeatureDataPath *string
}

type CreateForecastingExperimentResponse struct {
	// The unique ID of the created forecasting experiment
	ExperimentId *string
}

type CreateForecastingExperimentWaiter struct {
	// contains filtered or unexported fields
}

type ForecastingExperiment struct {
	// The unique ID for the forecasting experiment.
	ExperimentId *string
	// The URL to the forecasting experiment page.
	ExperimentPageUrl *string
	// The current state of the forecasting experiment.
	State ForecastingExperiment_State
}

type ForecastingExperiment_State string

type GetForecastingExperimentRequest struct {
	// The unique ID of a forecasting experiment
	ExperimentId *string
}