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types.go
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// Code generated by smithy-go-codegen DO NOT EDIT.
package types
import (
smithydocument "github.com/aws/smithy-go/document"
"time"
)
// Defines the modifications that you are making to an attribute for a what-if
// forecast. For example, you can use this operation to create a what-if forecast
// that investigates a 10% off sale on all shoes. To do this, you specify
// "AttributeName": "shoes" , "Operation": "MULTIPLY" , and "Value": "0.90" . Pair
// this operation with the TimeSeriesConditionoperation within the CreateWhatIfForecastRequest$TimeSeriesTransformations operation to define a subset of
// attribute items that are modified.
type Action struct {
// The related time series that you are modifying. This value is case insensitive.
//
// This member is required.
AttributeName *string
// The operation that is applied to the provided attribute. Operations include:
//
// - ADD - adds Value to all rows of AttributeName .
//
// - SUBTRACT - subtracts Value from all rows of AttributeName .
//
// - MULTIPLY - multiplies all rows of AttributeName by Value .
//
// - DIVIDE - divides all rows of AttributeName by Value .
//
// This member is required.
Operation Operation
// The value that is applied for the chosen Operation .
//
// This member is required.
Value *float64
noSmithyDocumentSerde
}
// Describes an additional dataset. This object is part of the DataConfig object. Forecast
// supports the Weather Index and Holidays additional datasets.
//
// # Weather Index
//
// The Amazon Forecast Weather Index is a built-in dataset that incorporates
// historical and projected weather information into your model. The Weather Index
// supplements your datasets with over two years of historical weather data and up
// to 14 days of projected weather data. For more information, see [Amazon Forecast Weather Index].
//
// # Holidays
//
// Holidays is a built-in dataset that incorporates national holiday information
// into your model. It provides native support for the holiday calendars of 66
// countries. To view the holiday calendars, refer to the [Jollyday]library. For more
// information, see [Holidays Featurization].
//
// [Amazon Forecast Weather Index]: https://docs.aws.amazon.com/forecast/latest/dg/weather.html
// [Jollyday]: http://jollyday.sourceforge.net/data.html
// [Holidays Featurization]: https://docs.aws.amazon.com/forecast/latest/dg/holidays.html
type AdditionalDataset struct {
// The name of the additional dataset. Valid names: "holiday" and "weather" .
//
// This member is required.
Name *string
// Weather Index
//
// To enable the Weather Index, do not specify a value for Configuration .
//
// Holidays
//
// Holidays
//
// To enable Holidays, set CountryCode to one of the following two-letter country
// codes:
//
// - "AL" - ALBANIA
//
// - "AR" - ARGENTINA
//
// - "AT" - AUSTRIA
//
// - "AU" - AUSTRALIA
//
// - "BA" - BOSNIA HERZEGOVINA
//
// - "BE" - BELGIUM
//
// - "BG" - BULGARIA
//
// - "BO" - BOLIVIA
//
// - "BR" - BRAZIL
//
// - "BY" - BELARUS
//
// - "CA" - CANADA
//
// - "CL" - CHILE
//
// - "CO" - COLOMBIA
//
// - "CR" - COSTA RICA
//
// - "HR" - CROATIA
//
// - "CZ" - CZECH REPUBLIC
//
// - "DK" - DENMARK
//
// - "EC" - ECUADOR
//
// - "EE" - ESTONIA
//
// - "ET" - ETHIOPIA
//
// - "FI" - FINLAND
//
// - "FR" - FRANCE
//
// - "DE" - GERMANY
//
// - "GR" - GREECE
//
// - "HU" - HUNGARY
//
// - "IS" - ICELAND
//
// - "IN" - INDIA
//
// - "IE" - IRELAND
//
// - "IT" - ITALY
//
// - "JP" - JAPAN
//
// - "KZ" - KAZAKHSTAN
//
// - "KR" - KOREA
//
// - "LV" - LATVIA
//
// - "LI" - LIECHTENSTEIN
//
// - "LT" - LITHUANIA
//
// - "LU" - LUXEMBOURG
//
// - "MK" - MACEDONIA
//
// - "MT" - MALTA
//
// - "MX" - MEXICO
//
// - "MD" - MOLDOVA
//
// - "ME" - MONTENEGRO
//
// - "NL" - NETHERLANDS
//
// - "NZ" - NEW ZEALAND
//
// - "NI" - NICARAGUA
//
// - "NG" - NIGERIA
//
// - "NO" - NORWAY
//
// - "PA" - PANAMA
//
// - "PY" - PARAGUAY
//
// - "PE" - PERU
//
// - "PL" - POLAND
//
// - "PT" - PORTUGAL
//
// - "RO" - ROMANIA
//
// - "RU" - RUSSIA
//
// - "RS" - SERBIA
//
// - "SK" - SLOVAKIA
//
// - "SI" - SLOVENIA
//
// - "ZA" - SOUTH AFRICA
//
// - "ES" - SPAIN
//
// - "SE" - SWEDEN
//
// - "CH" - SWITZERLAND
//
// - "UA" - UKRAINE
//
// - "AE" - UNITED ARAB EMIRATES
//
// - "US" - UNITED STATES
//
// - "UK" - UNITED KINGDOM
//
// - "UY" - URUGUAY
//
// - "VE" - VENEZUELA
Configuration map[string][]string
noSmithyDocumentSerde
}
// Provides information about the method used to transform attributes.
//
// The following is an example using the RETAIL domain:
//
// {
//
// "AttributeName": "demand",
//
// "Transformations": {"aggregation": "sum", "middlefill": "zero", "backfill":
// "zero"}
//
// }
type AttributeConfig struct {
// The name of the attribute as specified in the schema. Amazon Forecast supports
// the target field of the target time series and the related time series datasets.
// For example, for the RETAIL domain, the target is demand .
//
// This member is required.
AttributeName *string
// The method parameters (key-value pairs), which are a map of override
// parameters. Specify these parameters to override the default values. Related
// Time Series attributes do not accept aggregation parameters.
//
// The following list shows the parameters and their valid values for the
// "filling" featurization method for a Target Time Series dataset. Default values
// are bolded.
//
// - aggregation : sum, avg , first , min , max
//
// - frontfill : none
//
// - middlefill : zero, nan (not a number), value , median , mean , min , max
//
// - backfill : zero, nan , value , median , mean , min , max
//
// The following list shows the parameters and their valid values for a Related
// Time Series featurization method (there are no defaults):
//
// - middlefill : zero , value , median , mean , min , max
//
// - backfill : zero , value , median , mean , min , max
//
// - futurefill : zero , value , median , mean , min , max
//
// To set a filling method to a specific value, set the fill parameter to value
// and define the value in a corresponding _value parameter. For example, to set
// backfilling to a value of 2, include the following: "backfill": "value" and
// "backfill_value":"2" .
//
// This member is required.
Transformations map[string]string
noSmithyDocumentSerde
}
// Metrics you can use as a baseline for comparison purposes. Use these metrics
// when you interpret monitoring results for an auto predictor.
type Baseline struct {
// The initial [accuracy metrics] for the predictor you are monitoring. Use these metrics as a
// baseline for comparison purposes as you use your predictor and the metrics
// change.
//
// [accuracy metrics]: https://docs.aws.amazon.com/forecast/latest/dg/metrics.html
PredictorBaseline *PredictorBaseline
noSmithyDocumentSerde
}
// An individual metric that you can use for comparison as you evaluate your
// monitoring results.
type BaselineMetric struct {
// The name of the metric.
Name *string
// The value for the metric.
Value *float64
noSmithyDocumentSerde
}
// Specifies a categorical hyperparameter and it's range of tunable values. This
// object is part of the ParameterRangesobject.
type CategoricalParameterRange struct {
// The name of the categorical hyperparameter to tune.
//
// This member is required.
Name *string
// A list of the tunable categories for the hyperparameter.
//
// This member is required.
Values []string
noSmithyDocumentSerde
}
// Specifies a continuous hyperparameter and it's range of tunable values. This
// object is part of the ParameterRangesobject.
type ContinuousParameterRange struct {
// The maximum tunable value of the hyperparameter.
//
// This member is required.
MaxValue *float64
// The minimum tunable value of the hyperparameter.
//
// This member is required.
MinValue *float64
// The name of the hyperparameter to tune.
//
// This member is required.
Name *string
// The scale that hyperparameter tuning uses to search the hyperparameter range.
// Valid values:
//
// Auto Amazon Forecast hyperparameter tuning chooses the best scale for the
// hyperparameter.
//
// Linear Hyperparameter tuning searches the values in the hyperparameter range by
// using a linear scale.
//
// Logarithmic Hyperparameter tuning searches the values in the hyperparameter
// range by using a logarithmic scale.
//
// Logarithmic scaling works only for ranges that have values greater than 0.
//
// ReverseLogarithmic hyperparameter tuning searches the values in the
// hyperparameter range by using a reverse logarithmic scale.
//
// Reverse logarithmic scaling works only for ranges that are entirely within the
// range 0 <= x < 1.0.
//
// For information about choosing a hyperparameter scale, see [Hyperparameter Scaling]. One of the
// following values:
//
// [Hyperparameter Scaling]: http://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-type
ScalingType ScalingType
noSmithyDocumentSerde
}
// The data configuration for your dataset group and any additional datasets.
type DataConfig struct {
// The ARN of the dataset group used to train the predictor.
//
// This member is required.
DatasetGroupArn *string
// Additional built-in datasets like Holidays and the Weather Index.
AdditionalDatasets []AdditionalDataset
// Aggregation and filling options for attributes in your dataset group.
AttributeConfigs []AttributeConfig
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}
// The destination for an export job. Provide an S3 path, an Identity and Access
// Management (IAM) role that allows Amazon Forecast to access the location, and an
// Key Management Service (KMS) key (optional).
type DataDestination struct {
// The path to an Amazon Simple Storage Service (Amazon S3) bucket along with the
// credentials to access the bucket.
//
// This member is required.
S3Config *S3Config
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}
// Provides a summary of the dataset group properties used in the [ListDatasetGroups] operation. To
// get the complete set of properties, call the [DescribeDatasetGroup]operation, and provide the
// DatasetGroupArn .
//
// [ListDatasetGroups]: https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetGroups.html
// [DescribeDatasetGroup]: https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDatasetGroup.html
type DatasetGroupSummary struct {
// When the dataset group was created.
CreationTime *time.Time
// The Amazon Resource Name (ARN) of the dataset group.
DatasetGroupArn *string
// The name of the dataset group.
DatasetGroupName *string
// When the dataset group was created or last updated from a call to the [UpdateDatasetGroup]
// operation. While the dataset group is being updated, LastModificationTime is
// the current time of the ListDatasetGroups call.
//
// [UpdateDatasetGroup]: https://docs.aws.amazon.com/forecast/latest/dg/API_UpdateDatasetGroup.html
LastModificationTime *time.Time
noSmithyDocumentSerde
}
// Provides a summary of the dataset import job properties used in the [ListDatasetImportJobs] operation.
// To get the complete set of properties, call the [DescribeDatasetImportJob]operation, and provide the
// DatasetImportJobArn .
//
// [ListDatasetImportJobs]: https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetImportJobs.html
// [DescribeDatasetImportJob]: https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDatasetImportJob.html
type DatasetImportJobSummary struct {
// When the dataset import job was created.
CreationTime *time.Time
// The location of the training data to import and an Identity and Access
// Management (IAM) role that Amazon Forecast can assume to access the data. The
// training data must be stored in an Amazon S3 bucket.
//
// If encryption is used, DataSource includes an Key Management Service (KMS) key.
DataSource *DataSource
// The Amazon Resource Name (ARN) of the dataset import job.
DatasetImportJobArn *string
// The name of the dataset import job.
DatasetImportJobName *string
// The import mode of the dataset import job, FULL or INCREMENTAL.
ImportMode ImportMode
// The last time the resource was modified. The timestamp depends on the status of
// the job:
//
// - CREATE_PENDING - The CreationTime .
//
// - CREATE_IN_PROGRESS - The current timestamp.
//
// - CREATE_STOPPING - The current timestamp.
//
// - CREATE_STOPPED - When the job stopped.
//
// - ACTIVE or CREATE_FAILED - When the job finished or failed.
LastModificationTime *time.Time
// If an error occurred, an informational message about the error.
Message *string
// The status of the dataset import job. States include:
//
// - ACTIVE
//
// - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED
//
// - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED
//
// - CREATE_STOPPING , CREATE_STOPPED
Status *string
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}
// Provides a summary of the dataset properties used in the [ListDatasets] operation. To get the
// complete set of properties, call the [DescribeDataset]operation, and provide the DatasetArn .
//
// [DescribeDataset]: https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDataset.html
// [ListDatasets]: https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasets.html
type DatasetSummary struct {
// When the dataset was created.
CreationTime *time.Time
// The Amazon Resource Name (ARN) of the dataset.
DatasetArn *string
// The name of the dataset.
DatasetName *string
// The dataset type.
DatasetType DatasetType
// The domain associated with the dataset.
Domain Domain
// When you create a dataset, LastModificationTime is the same as CreationTime .
// While data is being imported to the dataset, LastModificationTime is the
// current time of the ListDatasets call. After a [CreateDatasetImportJob] operation has finished,
// LastModificationTime is when the import job completed or failed.
//
// [CreateDatasetImportJob]: https://docs.aws.amazon.com/forecast/latest/dg/API_CreateDatasetImportJob.html
LastModificationTime *time.Time
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}
// The source of your data, an Identity and Access Management (IAM) role that
// allows Amazon Forecast to access the data and, optionally, an Key Management
// Service (KMS) key.
type DataSource struct {
// The path to the data stored in an Amazon Simple Storage Service (Amazon S3)
// bucket along with the credentials to access the data.
//
// This member is required.
S3Config *S3Config
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}
// An Key Management Service (KMS) key and an Identity and Access Management (IAM)
// role that Amazon Forecast can assume to access the key. You can specify this
// optional object in the CreateDatasetand CreatePredictor requests.
type EncryptionConfig struct {
// The Amazon Resource Name (ARN) of the KMS key.
//
// This member is required.
KMSKeyArn *string
// The ARN of the IAM role that Amazon Forecast can assume to access the KMS key.
//
// Passing a role across Amazon Web Services accounts is not allowed. If you pass
// a role that isn't in your account, you get an InvalidInputException error.
//
// This member is required.
RoleArn *string
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}
// Provides detailed error metrics to evaluate the performance of a predictor.
//
// This object is part of the Metricsobject.
type ErrorMetric struct {
// The Forecast type used to compute WAPE, MAPE, MASE, and RMSE.
ForecastType *string
// The Mean Absolute Percentage Error (MAPE)
MAPE *float64
// The Mean Absolute Scaled Error (MASE)
MASE *float64
// The root-mean-square error (RMSE).
RMSE *float64
// The weighted absolute percentage error (WAPE).
WAPE *float64
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}
// Parameters that define how to split a dataset into training data and testing
// data, and the number of iterations to perform. These parameters are specified in
// the predefined algorithms but you can override them in the CreatePredictorrequest.
type EvaluationParameters struct {
// The point from the end of the dataset where you want to split the data for
// model training and testing (evaluation). Specify the value as the number of data
// points. The default is the value of the forecast horizon. BackTestWindowOffset
// can be used to mimic a past virtual forecast start date. This value must be
// greater than or equal to the forecast horizon and less than half of the
// TARGET_TIME_SERIES dataset length.
//
// ForecastHorizon <= BackTestWindowOffset < 1/2 * TARGET_TIME_SERIES dataset
// length
BackTestWindowOffset *int32
// The number of times to split the input data. The default is 1. Valid values are
// 1 through 5.
NumberOfBacktestWindows *int32
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}
// The results of evaluating an algorithm. Returned as part of the GetAccuracyMetrics response.
type EvaluationResult struct {
// The Amazon Resource Name (ARN) of the algorithm that was evaluated.
AlgorithmArn *string
// The array of test windows used for evaluating the algorithm. The
// NumberOfBacktestWindows from the EvaluationParameters object determines the number of windows in
// the array.
TestWindows []WindowSummary
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}
// The ExplainabilityConfig data type defines the number of time series and time
// points included in CreateExplainability.
//
// If you provide a predictor ARN for ResourceArn , you must set both
// TimePointGranularity and TimeSeriesGranularity to “ALL”. When creating
// Predictor Explainability, Amazon Forecast considers all time series and time
// points.
//
// If you provide a forecast ARN for ResourceArn , you can set TimePointGranularity
// and TimeSeriesGranularity to either “ALL” or “Specific”.
type ExplainabilityConfig struct {
// To create an Explainability for all time points in your forecast horizon, use
// ALL . To create an Explainability for specific time points in your forecast
// horizon, use SPECIFIC .
//
// Specify time points with the StartDateTime and EndDateTime parameters within
// the CreateExplainabilityoperation.
//
// This member is required.
TimePointGranularity TimePointGranularity
// To create an Explainability for all time series in your datasets, use ALL . To
// create an Explainability for specific time series in your datasets, use SPECIFIC
// .
//
// Specify time series by uploading a CSV or Parquet file to an Amazon S3 bucket
// and set the location within the DataDestinationdata type.
//
// This member is required.
TimeSeriesGranularity TimeSeriesGranularity
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}
// Provides a summary of the Explainability export properties used in the ListExplainabilityExports
// operation. To get a complete set of properties, call the DescribeExplainabilityExportoperation, and provide
// the ExplainabilityExportArn .
type ExplainabilityExportSummary struct {
// When the Explainability was created.
CreationTime *time.Time
// The destination for an export job. Provide an S3 path, an Identity and Access
// Management (IAM) role that allows Amazon Forecast to access the location, and an
// Key Management Service (KMS) key (optional).
Destination *DataDestination
// The Amazon Resource Name (ARN) of the Explainability export.
ExplainabilityExportArn *string
// The name of the Explainability export
ExplainabilityExportName *string
// The last time the resource was modified. The timestamp depends on the status of
// the job:
//
// - CREATE_PENDING - The CreationTime .
//
// - CREATE_IN_PROGRESS - The current timestamp.
//
// - CREATE_STOPPING - The current timestamp.
//
// - CREATE_STOPPED - When the job stopped.
//
// - ACTIVE or CREATE_FAILED - When the job finished or failed.
LastModificationTime *time.Time
// Information about any errors that may have occurred during the Explainability
// export.
Message *string
// The status of the Explainability export. States include:
//
// - ACTIVE
//
// - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED
//
// - CREATE_STOPPING , CREATE_STOPPED
//
// - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED
Status *string
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}
// Provides information about the Explainability resource.
type ExplainabilityInfo struct {
// The Amazon Resource Name (ARN) of the Explainability.
ExplainabilityArn *string
// The status of the Explainability. States include:
//
// - ACTIVE
//
// - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED
//
// - CREATE_STOPPING , CREATE_STOPPED
//
// - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED
Status *string
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}
// Provides a summary of the Explainability properties used in the ListExplainabilities operation. To
// get a complete set of properties, call the DescribeExplainabilityoperation, and provide the listed
// ExplainabilityArn .
type ExplainabilitySummary struct {
// When the Explainability was created.
CreationTime *time.Time
// The Amazon Resource Name (ARN) of the Explainability.
ExplainabilityArn *string
// The configuration settings that define the granularity of time series and time
// points for the Explainability.
ExplainabilityConfig *ExplainabilityConfig
// The name of the Explainability.
ExplainabilityName *string
// The last time the resource was modified. The timestamp depends on the status of
// the job:
//
// - CREATE_PENDING - The CreationTime .
//
// - CREATE_IN_PROGRESS - The current timestamp.
//
// - CREATE_STOPPING - The current timestamp.
//
// - CREATE_STOPPED - When the job stopped.
//
// - ACTIVE or CREATE_FAILED - When the job finished or failed.
LastModificationTime *time.Time
// Information about any errors that may have occurred during the Explainability
// creation process.
Message *string
// The Amazon Resource Name (ARN) of the Predictor or Forecast used to create the
// Explainability.
ResourceArn *string
// The status of the Explainability. States include:
//
// - ACTIVE
//
// - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED
//
// - CREATE_STOPPING , CREATE_STOPPED
//
// - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED
Status *string
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}
// This object belongs to the CreatePredictor operation. If you created your predictor with CreateAutoPredictor, see AttributeConfig
// .
//
// Provides featurization (transformation) information for a dataset field. This
// object is part of the FeaturizationConfigobject.
//
// For example:
//
// {
//
// "AttributeName": "demand",
//
// FeaturizationPipeline [ {
//
// "FeaturizationMethodName": "filling",
//
// "FeaturizationMethodParameters": {"aggregation": "avg", "backfill": "nan"}
//
// } ]
//
// }
type Featurization struct {
// The name of the schema attribute that specifies the data field to be
// featurized. Amazon Forecast supports the target field of the TARGET_TIME_SERIES
// and the RELATED_TIME_SERIES datasets. For example, for the RETAIL domain, the
// target is demand , and for the CUSTOM domain, the target is target_value . For
// more information, see howitworks-missing-values.
//
// This member is required.
AttributeName *string
// An array of one FeaturizationMethod object that specifies the feature
// transformation method.
FeaturizationPipeline []FeaturizationMethod
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}
// This object belongs to the CreatePredictor operation. If you created your predictor with CreateAutoPredictor, see AttributeConfig
// .
//
// In a CreatePredictor operation, the specified algorithm trains a model using the specified
// dataset group. You can optionally tell the operation to modify data fields prior
// to training a model. These modifications are referred to as featurization.
//
// You define featurization using the FeaturizationConfig object. You specify an
// array of transformations, one for each field that you want to featurize. You
// then include the FeaturizationConfig object in your CreatePredictor request.
// Amazon Forecast applies the featurization to the TARGET_TIME_SERIES and
// RELATED_TIME_SERIES datasets before model training.
//
// You can create multiple featurization configurations. For example, you might
// call the CreatePredictor operation twice by specifying different featurization
// configurations.
type FeaturizationConfig struct {
// 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. You cannot specify a value that would
// overlap with the next larger frequency. That means, for example, you cannot
// specify a frequency of 60 minutes, because that is equivalent to 1 hour. 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
//
// Thus, if you want every other week forecasts, specify "2W". Or, if you want
// quarterly forecasts, you specify "3M".
//
// The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset
// frequency.
//
// When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to
// the TARGET_TIME_SERIES dataset frequency.
//
// This member is required.
ForecastFrequency *string
// An array of featurization (transformation) information for the fields of a
// dataset.
Featurizations []Featurization
// An array of dimension (field) names that specify how to group the generated
// forecast.
//
// For example, suppose that you are generating a forecast for item sales across
// all of your stores, and your dataset contains a store_id field. If you want the
// sales forecast for each item by store, you would specify store_id as the
// dimension.
//
// All forecast dimensions specified in the TARGET_TIME_SERIES dataset don't need
// to be specified in the CreatePredictor request. All forecast dimensions
// specified in the RELATED_TIME_SERIES dataset must be specified in the
// CreatePredictor request.
ForecastDimensions []string
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}
// Provides information about the method that featurizes (transforms) a dataset
// field. The method is part of the FeaturizationPipeline of the Featurization object.
//
// The following is an example of how you specify a FeaturizationMethod object.
//
// {
//
// "FeaturizationMethodName": "filling",
//
// "FeaturizationMethodParameters": {"aggregation": "sum", "middlefill": "zero",
// "backfill": "zero"}
//
// }
type FeaturizationMethod struct {
// The name of the method. The "filling" method is the only supported method.
//
// This member is required.
FeaturizationMethodName FeaturizationMethodName
// The method parameters (key-value pairs), which are a map of override
// parameters. Specify these parameters to override the default values. Related
// Time Series attributes do not accept aggregation parameters.
//
// The following list shows the parameters and their valid values for the
// "filling" featurization method for a Target Time Series dataset. Bold signifies
// the default value.
//
// - aggregation : sum, avg , first , min , max
//
// - frontfill : none
//
// - middlefill : zero, nan (not a number), value , median , mean , min , max
//
// - backfill : zero, nan , value , median , mean , min , max
//
// The following list shows the parameters and their valid values for a Related
// Time Series featurization method (there are no defaults):
//
// - middlefill : zero , value , median , mean , min , max
//
// - backfill : zero , value , median , mean , min , max
//
// - futurefill : zero , value , median , mean , min , max
//
// To set a filling method to a specific value, set the fill parameter to value
// and define the value in a corresponding _value parameter. For example, to set
// backfilling to a value of 2, include the following: "backfill": "value" and
// "backfill_value":"2" .
FeaturizationMethodParameters map[string]string
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}
// Describes a filter for choosing a subset of objects. Each filter consists of a
// condition and a match statement. The condition is either IS or IS_NOT , which
// specifies whether to include or exclude the objects that match the statement,
// respectively. The match statement consists of a key and a value.
type Filter struct {
// The condition to apply. To include the objects that match the statement,
// specify IS . To exclude matching objects, specify IS_NOT .
//
// This member is required.
Condition FilterConditionString
// The name of the parameter to filter on.
//
// This member is required.
Key *string
// The value to match.
//
// This member is required.
Value *string
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}
// Provides a summary of the forecast export job properties used in the ListForecastExportJobs
// operation. To get the complete set of properties, call the DescribeForecastExportJoboperation, and
// provide the listed ForecastExportJobArn .
type ForecastExportJobSummary struct {
// When the forecast export job was created.
CreationTime *time.Time
// The path to the Amazon Simple Storage Service (Amazon S3) bucket where the
// forecast is exported.
Destination *DataDestination
// The Amazon Resource Name (ARN) of the forecast export job.
ForecastExportJobArn *string
// The name of the forecast export job.
ForecastExportJobName *string
// The last time the resource was modified. The timestamp depends on the status of
// the job:
//
// - CREATE_PENDING - The CreationTime .
//
// - CREATE_IN_PROGRESS - The current timestamp.
//
// - CREATE_STOPPING - The current timestamp.
//
// - CREATE_STOPPED - When the job stopped.
//
// - ACTIVE or CREATE_FAILED - When the job finished or failed.
LastModificationTime *time.Time
// If an error occurred, an informational message about the error.
Message *string
// The status of the forecast export job. States include:
//
// - ACTIVE
//
// - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED