// 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 TimeSeriesCondition operation 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 (https://docs.aws.amazon.com/forecast/latest/dg/weather.html) . // 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 (http://jollyday.sourceforge.net/data.html) // library. For more information, see 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 (https://docs.aws.amazon.com/forecast/latest/dg/metrics.html) // for the predictor you are monitoring. Use these metrics as a baseline for // comparison purposes as you use your predictor and the metrics change. 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 ParameterRanges object. 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 ParameterRanges object. 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 (http://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-type) // . One of the following values: 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 noSmithyDocumentSerde } // 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 noSmithyDocumentSerde } // Provides a summary of the dataset group properties used in the ListDatasetGroups (https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetGroups.html) // operation. To get the complete set of properties, call the DescribeDatasetGroup (https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDatasetGroup.html) // operation, and provide the DatasetGroupArn . 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 (https://docs.aws.amazon.com/forecast/latest/dg/API_UpdateDatasetGroup.html) // operation. While the dataset group is being updated, LastModificationTime is // the current time of the ListDatasetGroups call. LastModificationTime *time.Time noSmithyDocumentSerde } // Provides a summary of the dataset import job properties used in the // ListDatasetImportJobs (https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetImportJobs.html) // operation. To get the complete set of properties, call the // DescribeDatasetImportJob (https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDatasetImportJob.html) // operation, and provide the DatasetImportJobArn . 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 noSmithyDocumentSerde } // Provides a summary of the dataset properties used in the ListDatasets (https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasets.html) // operation. To get the complete set of properties, call the DescribeDataset (https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDataset.html) // operation, and provide the DatasetArn . 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 (https://docs.aws.amazon.com/forecast/latest/dg/API_CreateDatasetImportJob.html) // operation has finished, LastModificationTime is when the import job completed // or failed. LastModificationTime *time.Time noSmithyDocumentSerde } // 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 noSmithyDocumentSerde } // 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 CreateDataset and 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 noSmithyDocumentSerde } // Provides detailed error metrics to evaluate the performance of a predictor. // This object is part of the Metrics object. 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 noSmithyDocumentSerde } // 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 CreatePredictor // request. 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 noSmithyDocumentSerde } // 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 noSmithyDocumentSerde } // 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 “ALLâ€. 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 // “Specificâ€. 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 CreateExplainability operation. // // 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 DataDestination data type. // // This member is required. TimeSeriesGranularity TimeSeriesGranularity noSmithyDocumentSerde } // Provides a summary of the Explainability export properties used in the // ListExplainabilityExports operation. To get a complete set of properties, call // the DescribeExplainabilityExport operation, 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 noSmithyDocumentSerde } // 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 noSmithyDocumentSerde } // Provides a summary of the Explainability properties used in the // ListExplainabilities operation. To get a complete set of properties, call the // DescribeExplainability operation, 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 noSmithyDocumentSerde } // 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 FeaturizationConfig object. 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 noSmithyDocumentSerde } // 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 noSmithyDocumentSerde } // 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 noSmithyDocumentSerde } // 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 noSmithyDocumentSerde } // Provides a summary of the forecast export job properties used in the // ListForecastExportJobs operation. To get the complete set of properties, call // the DescribeForecastExportJob operation, 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 // - CREATE_STOPPING , CREATE_STOPPED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED // The Status of the forecast export job must be ACTIVE before you can access the // forecast in your S3 bucket. Status *string noSmithyDocumentSerde } // Provides a summary of the forecast properties used in the ListForecasts // operation. To get the complete set of properties, call the DescribeForecast // operation, and provide the ForecastArn that is listed in the summary. type ForecastSummary struct { // Whether the Forecast was created from an AutoPredictor. CreatedUsingAutoPredictor *bool // When the forecast creation task was created. CreationTime *time.Time // The Amazon Resource Name (ARN) of the dataset group that provided the data used // to train the predictor. DatasetGroupArn *string // The ARN of the forecast. ForecastArn *string // The name of the forecast. ForecastName *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 ARN of the predictor used to generate the forecast. PredictorArn *string // The status of the forecast. States include: // - ACTIVE // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - CREATE_STOPPING , CREATE_STOPPED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED // The Status of the forecast must be ACTIVE before you can query or export the // forecast. Status *string noSmithyDocumentSerde } // Configuration information for a hyperparameter tuning job. You specify this // object in the CreatePredictor request. A hyperparameter is a parameter that // governs the model training process. You set hyperparameters before training // starts, unlike model parameters, which are determined during training. The // values of the hyperparameters effect which values are chosen for the model // parameters. In a hyperparameter tuning job, Amazon Forecast chooses the set of // hyperparameter values that optimize a specified metric. Forecast accomplishes // this by running many training jobs over a range of hyperparameter values. The // optimum set of values depends on the algorithm, the training data, and the // specified metric objective. type HyperParameterTuningJobConfig struct { // Specifies the ranges of valid values for the hyperparameters. ParameterRanges *ParameterRanges noSmithyDocumentSerde } // This object belongs to the CreatePredictor operation. If you created your // predictor with CreateAutoPredictor , see DataConfig . The data used to train a // predictor. The data includes a dataset group and any supplementary features. You // specify this object in the CreatePredictor request. type InputDataConfig struct { // The Amazon Resource Name (ARN) of the dataset group. // // This member is required. DatasetGroupArn *string // An array of supplementary features. The only supported feature is a holiday // calendar. SupplementaryFeatures []SupplementaryFeature noSmithyDocumentSerde } // Specifies an integer hyperparameter and it's range of tunable values. This // object is part of the ParameterRanges object. type IntegerParameterRange struct { // The maximum tunable value of the hyperparameter. // // This member is required. MaxValue *int32 // The minimum tunable value of the hyperparameter. // // This member is required. MinValue *int32 // 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 Not supported for IntegerParameterRange . 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 (http://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-type) // . One of the following values: ScalingType ScalingType noSmithyDocumentSerde } // An individual metric Forecast calculated when monitoring predictor usage. You // can compare the value for this metric to the metric's value in the Baseline to // see how your predictor's performance is changing. For more information about // metrics generated by Forecast see Evaluating Predictor Accuracy (https://docs.aws.amazon.com/forecast/latest/dg/metrics.html) type MetricResult struct { // The name of the metric. MetricName *string // The value for the metric. MetricValue *float64 noSmithyDocumentSerde } // Provides metrics that are used to evaluate the performance of a predictor. This // object is part of the WindowSummary object. type Metrics struct { // The average value of all weighted quantile losses. AverageWeightedQuantileLoss *float64 // Provides detailed error metrics for each forecast type. Metrics include // root-mean square-error (RMSE), mean absolute percentage error (MAPE), mean // absolute scaled error (MASE), and weighted average percentage error (WAPE). ErrorMetrics []ErrorMetric // The root-mean-square error (RMSE). // // Deprecated: This property is deprecated, please refer to ErrorMetrics for both // RMSE and WAPE RMSE *float64 // An array of weighted quantile losses. Quantiles divide a probability // distribution into regions of equal probability. The distribution in this case is // the loss function. WeightedQuantileLosses []WeightedQuantileLoss noSmithyDocumentSerde } // The configuration details for the predictor monitor. type MonitorConfig struct { // The name of the monitor resource. // // This member is required. MonitorName *string noSmithyDocumentSerde } // The source of the data the monitor used during the evaluation. type MonitorDataSource struct { // The Amazon Resource Name (ARN) of the dataset import job used to import the // data that initiated the monitor evaluation. DatasetImportJobArn *string // The Amazon Resource Name (ARN) of the forecast the monitor used during the // evaluation. ForecastArn *string // The Amazon Resource Name (ARN) of the predictor resource you are monitoring. PredictorArn *string noSmithyDocumentSerde } // Provides information about the monitor resource. type MonitorInfo struct { // The Amazon Resource Name (ARN) of the monitor resource. MonitorArn *string // The status of the monitor. States include: // - ACTIVE // - ACTIVE_STOPPING , ACTIVE_STOPPED // - UPDATE_IN_PROGRESS // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED Status *string noSmithyDocumentSerde } // Provides a summary of the monitor properties used in the ListMonitors // operation. To get a complete set of properties, call the DescribeMonitor // operation, and provide the listed MonitorArn . type MonitorSummary struct { // When the monitor resource was created. CreationTime *time.Time // The last time the monitor resource was modified. The timestamp depends on the // status of the job: // - CREATE_PENDING - The CreationTime . // - CREATE_IN_PROGRESS - The current timestamp. // - STOPPED - When the resource stopped. // - ACTIVE or CREATE_FAILED - When the monitor creation finished or failed. LastModificationTime *time.Time // The Amazon Resource Name (ARN) of the monitor resource. MonitorArn *string // The name of the monitor resource. MonitorName *string // The Amazon Resource Name (ARN) of the predictor being monitored. ResourceArn *string // The status of the monitor. States include: // - ACTIVE // - ACTIVE_STOPPING , ACTIVE_STOPPED // - UPDATE_IN_PROGRESS // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED Status *string noSmithyDocumentSerde } // Specifies the categorical, continuous, and integer hyperparameters, and their // ranges of tunable values. The range of tunable values determines which values // that a hyperparameter tuning job can choose for the specified hyperparameter. // This object is part of the HyperParameterTuningJobConfig object. type ParameterRanges struct { // Specifies the tunable range for each categorical hyperparameter. CategoricalParameterRanges []CategoricalParameterRange // Specifies the tunable range for each continuous hyperparameter. ContinuousParameterRanges []ContinuousParameterRange // Specifies the tunable range for each integer hyperparameter. IntegerParameterRanges []IntegerParameterRange noSmithyDocumentSerde } // Provides a summary of the predictor backtest export job properties used in the // ListPredictorBacktestExportJobs operation. To get a complete set of properties, // call the DescribePredictorBacktestExportJob operation, and provide the listed // PredictorBacktestExportJobArn . type PredictorBacktestExportJobSummary struct { // When the predictor backtest export job 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 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 backtest export. Message *string // The Amazon Resource Name (ARN) of the predictor backtest export job. PredictorBacktestExportJobArn *string // The name of the predictor backtest export job. PredictorBacktestExportJobName *string // The status of the predictor backtest export job. States include: // - ACTIVE // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - CREATE_STOPPING , CREATE_STOPPED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED Status *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 PredictorBaseline struct { // The initial accuracy metrics (https://docs.aws.amazon.com/forecast/latest/dg/metrics.html) // for the predictor. Use these metrics as a baseline for comparison purposes as // you use your predictor and the metrics change. BaselineMetrics []BaselineMetric noSmithyDocumentSerde } // Provides details about a predictor event, such as a retraining. type PredictorEvent struct { // The timestamp for when the event occurred. Datetime *time.Time // The type of event. For example, Retrain . A retraining event denotes the // timepoint when a predictor was retrained. Any monitor results from before the // Datetime are from the previous predictor. Any new metrics are for the newly // retrained predictor. Detail *string noSmithyDocumentSerde } // The algorithm used to perform a backtest and the status of those tests. type PredictorExecution struct { // The ARN of the algorithm used to test the predictor. AlgorithmArn *string // An array of test windows used to evaluate the algorithm. The // NumberOfBacktestWindows from the object determines the number of windows in the // array. TestWindows []TestWindowSummary noSmithyDocumentSerde } // Contains details on the backtests performed to evaluate the accuracy of the // predictor. The tests are returned in descending order of accuracy, with the most // accurate backtest appearing first. You specify the number of backtests to // perform when you call the operation. type PredictorExecutionDetails struct { // An array of the backtests performed to evaluate the accuracy of the predictor // against a particular algorithm. The NumberOfBacktestWindows from the object // determines the number of windows in the array. PredictorExecutions []PredictorExecution noSmithyDocumentSerde } // Describes the results of a monitor evaluation. type PredictorMonitorEvaluation struct { // The status of the monitor evaluation. The state can be SUCCESS or FAILURE . EvaluationState *string // The timestamp that indicates when the monitor evaluation was started. EvaluationTime *time.Time // Information about any errors that may have occurred during the monitor // evaluation. Message *string // A list of metrics Forecast calculated when monitoring a predictor. You can // compare the value for each metric in the list to the metric's value in the // Baseline to see how your predictor's performance is changing. MetricResults []MetricResult // The Amazon Resource Name (ARN) of the monitor resource. MonitorArn *string // The source of the data the monitor resource used during the evaluation. MonitorDataSource *MonitorDataSource // The number of items considered during the evaluation. NumItemsEvaluated *int64 // Provides details about a predictor event, such as a retraining. PredictorEvent *PredictorEvent // The Amazon Resource Name (ARN) of the resource to monitor. ResourceArn *string // The timestamp that indicates the end of the window that is used for monitor // evaluation. WindowEndDatetime *time.Time // The timestamp that indicates the start of the window that is used for monitor // evaluation. WindowStartDatetime *time.Time noSmithyDocumentSerde } // Provides a summary of the predictor properties that are used in the // ListPredictors operation. To get the complete set of properties, call the // DescribePredictor operation, and provide the listed PredictorArn . type PredictorSummary struct { // When the model training task was created. CreationTime *time.Time // The Amazon Resource Name (ARN) of the dataset group that contains the data used // to train the predictor. DatasetGroupArn *string // Whether AutoPredictor was used to create the predictor. IsAutoPredictor *bool // 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 ARN of the predictor. PredictorArn *string // The name of the predictor. PredictorName *string // A summary of the reference predictor used if the predictor was retrained or // upgraded. ReferencePredictorSummary *ReferencePredictorSummary // The status of the predictor. States include: // - ACTIVE // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED // - CREATE_STOPPING , CREATE_STOPPED // The Status of the predictor must be ACTIVE before you can use the predictor to // create a forecast. Status *string noSmithyDocumentSerde } // Provides a summary of the reference predictor used when retraining or upgrading // a predictor. type ReferencePredictorSummary struct { // The ARN of the reference predictor. Arn *string // Whether the reference predictor is Active or Deleted . State State noSmithyDocumentSerde } // The path to the file(s) in an Amazon Simple Storage Service (Amazon S3) bucket, // and an Identity and Access Management (IAM) role that Amazon Forecast can assume // to access the file(s). Optionally, includes an Key Management Service (KMS) key. // This object is part of the DataSource object that is submitted in the // CreateDatasetImportJob request, and part of the DataDestination object. type S3Config struct { // The path to an Amazon Simple Storage Service (Amazon S3) bucket or file(s) in // an Amazon S3 bucket. // // This member is required. Path *string // The ARN of the Identity and Access Management (IAM) role that Amazon Forecast // can assume to access the Amazon S3 bucket or files. If you provide a value for // the KMSKeyArn key, the role must allow access to the 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 // The Amazon Resource Name (ARN) of an Key Management Service (KMS) key. KMSKeyArn *string noSmithyDocumentSerde } // Defines the fields of a dataset. type Schema struct { // An array of attributes specifying the name and type of each field in a dataset. Attributes []SchemaAttribute noSmithyDocumentSerde } // An attribute of a schema, which defines a dataset field. A schema attribute is // required for every field in a dataset. The Schema (https://docs.aws.amazon.com/forecast/latest/dg/API_Schema.html) // object contains an array of SchemaAttribute objects. type SchemaAttribute struct { // The name of the dataset field. AttributeName *string // The data type of the field. For a related time series dataset, other than date, // item_id, and forecast dimensions attributes, all attributes should be of // numerical type (integer/float). AttributeType AttributeType noSmithyDocumentSerde } // Provides statistics for each data field imported into to an Amazon Forecast // dataset with the CreateDatasetImportJob (https://docs.aws.amazon.com/forecast/latest/dg/API_CreateDatasetImportJob.html) // operation. type Statistics struct { // For a numeric field, the average value in the field. Avg *float64 // The number of values in the field. If the response value is -1, refer to // CountLong . Count *int32 // The number of distinct values in the field. If the response value is -1, refer // to CountDistinctLong . CountDistinct *int32 // The number of distinct values in the field. CountDistinctLong is used instead // of CountDistinct if the value is greater than 2,147,483,647. CountDistinctLong *int64 // The number of values in the field. CountLong is used instead of Count if the // value is greater than 2,147,483,647. CountLong *int64 // The number of NAN (not a number) values in the field. If the response value is // -1, refer to CountNanLong . CountNan *int32 // The number of NAN (not a number) values in the field. CountNanLong is used // instead of CountNan if the value is greater than 2,147,483,647. CountNanLong *int64 // The number of null values in the field. If the response value is -1, refer to // CountNullLong . CountNull *int32 // The number of null values in the field. CountNullLong is used instead of // CountNull if the value is greater than 2,147,483,647. CountNullLong *int64 // For a numeric field, the maximum value in the field. Max *string // For a numeric field, the minimum value in the field. Min *string // For a numeric field, the standard deviation. Stddev *float64 noSmithyDocumentSerde } // This object belongs to the CreatePredictor operation. If you created your // predictor with CreateAutoPredictor , see AdditionalDataset . Describes a // supplementary feature of a dataset group. This object is part of the // InputDataConfig object. Forecast supports the Weather Index and Holidays // built-in featurizations. Weather Index The Amazon Forecast Weather Index is a // built-in featurization 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 (https://docs.aws.amazon.com/forecast/latest/dg/weather.html) // . Holidays Holidays is a built-in featurization that incorporates a // feature-engineered dataset of 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 (http://jollyday.sourceforge.net/data.html) // library. For more information, see Holidays Featurization (https://docs.aws.amazon.com/forecast/latest/dg/holidays.html) // . type SupplementaryFeature struct { // The name of the feature. Valid values: "holiday" and "weather" . // // This member is required. Name *string // Weather Index To enable the Weather Index, set the value to "true" Holidays To // enable Holidays, specify a country with 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 // // This member is required. Value *string noSmithyDocumentSerde } // The optional metadata that you apply to a resource to help you categorize and // organize them. Each tag consists of a key and an optional value, both of which // you define. The following basic restrictions apply to tags: // - Maximum number of tags per resource - 50. // - For each resource, each tag key must be unique, and each tag key can have // only one value. // - Maximum key length - 128 Unicode characters in UTF-8. // - Maximum value length - 256 Unicode characters in UTF-8. // - If your tagging schema is used across multiple services and resources, // remember that other services may have restrictions on allowed characters. // Generally allowed characters are: letters, numbers, and spaces representable in // UTF-8, and the following characters: + - = . _ : / @. // - Tag keys and values are case sensitive. // - Do not use aws: , AWS: , or any upper or lowercase combination of such as a // prefix for keys as it is reserved for Amazon Web Services use. You cannot edit // or delete tag keys with this prefix. Values can have this prefix. If a tag value // has aws as its prefix but the key does not, then Forecast considers it to be a // user tag and will count against the limit of 50 tags. Tags with only the key // prefix of aws do not count against your tags per resource limit. type Tag struct { // One part of a key-value pair that makes up a tag. A key is a general label that // acts like a category for more specific tag values. // // This member is required. Key *string // The optional part of a key-value pair that makes up a tag. A value acts as a // descriptor within a tag category (key). // // This member is required. Value *string noSmithyDocumentSerde } // The status, start time, and end time of a backtest, as well as a failure reason // if applicable. type TestWindowSummary struct { // If the test failed, the reason why it failed. Message *string // The status of the test. Possible status values are: // - ACTIVE // - CREATE_IN_PROGRESS // - CREATE_FAILED Status *string // The time at which the test ended. TestWindowEnd *time.Time // The time at which the test began. TestWindowStart *time.Time noSmithyDocumentSerde } // The time boundary Forecast uses to align and aggregate your data to match your // forecast frequency. Provide the unit of time and the time boundary as a key // value pair. If you don't provide a time boundary, Forecast uses a set of // Default Time Boundaries (https://docs.aws.amazon.com/forecast/latest/dg/data-aggregation.html#default-time-boundaries) // . For more information about aggregation, see Data Aggregation for Different // Forecast Frequencies (https://docs.aws.amazon.com/forecast/latest/dg/data-aggregation.html) // . For more information setting a custom time boundary, see Specifying a Time // Boundary (https://docs.aws.amazon.com/forecast/latest/dg/data-aggregation.html#specifying-time-boundary) // . type TimeAlignmentBoundary struct { // The day of the month to use for time alignment during aggregation. DayOfMonth *int32 // The day of week to use for time alignment during aggregation. The day must be // in uppercase. DayOfWeek DayOfWeek // The hour of day to use for time alignment during aggregation. Hour *int32 // The month to use for time alignment during aggregation. The month must be in // uppercase. Month Month noSmithyDocumentSerde } // Creates a subset of items within an attribute that are modified. For example, // you can use this operation to create a subset of items that cost $5 or less. To // do this, you specify "AttributeName": "price" , "AttributeValue": "5" , and // "Condition": "LESS_THAN" . Pair this operation with the Action operation within // the CreateWhatIfForecastRequest$TimeSeriesTransformations operation to define // how the attribute is modified. type TimeSeriesCondition struct { // The item_id, dimension name, IM name, or timestamp that you are modifying. // // This member is required. AttributeName *string // The value that is applied for the chosen Condition . // // This member is required. AttributeValue *string // The condition to apply. Valid values are EQUALS , NOT_EQUALS , LESS_THAN and // GREATER_THAN . // // This member is required. Condition Condition noSmithyDocumentSerde } // Details about the import file that contains the time series for which you want // to create forecasts. type TimeSeriesIdentifiers struct { // 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. DataSource *DataSource // The format of the data, either CSV or PARQUET. Format *string // Defines the fields of a dataset. Schema *Schema noSmithyDocumentSerde } // A replacement dataset is a modified version of the baseline related time series // that contains only the values that you want to include in a what-if forecast. // The replacement dataset must contain the forecast dimensions and item // identifiers in the baseline related time series as well as at least 1 changed // time series. This dataset is merged with the baseline related time series to // create a transformed dataset that is used for the what-if forecast. type TimeSeriesReplacementsDataSource struct { // The path to the file(s) in an Amazon Simple Storage Service (Amazon S3) bucket, // and an Identity and Access Management (IAM) role that Amazon Forecast can assume // to access the file(s). Optionally, includes an Key Management Service (KMS) key. // This object is part of the DataSource object that is submitted in the // CreateDatasetImportJob request, and part of the DataDestination object. // // This member is required. S3Config *S3Config // Defines the fields of a dataset. // // This member is required. Schema *Schema // The format of the replacement data, CSV or PARQUET. Format *string // The timestamp format of the replacement data. TimestampFormat *string noSmithyDocumentSerde } // Defines the set of time series that are used to create the forecasts in a // TimeSeriesIdentifiers object. The TimeSeriesIdentifiers object needs the // following information: // - DataSource // - Format // - Schema type TimeSeriesSelector struct { // Details about the import file that contains the time series for which you want // to create forecasts. TimeSeriesIdentifiers *TimeSeriesIdentifiers noSmithyDocumentSerde } // A transformation function is a pair of operations that select and modify the // rows in a related time series. You select the rows that you want with a // condition operation and you modify the rows with a transformation operation. All // conditions are joined with an AND operation, meaning that all conditions must be // true for the transformation to be applied. Transformations are applied in the // order that they are listed. type TimeSeriesTransformation struct { // An array of actions that define a time series and how it is transformed. These // transformations create a new time series that is used for the what-if analysis. Action *Action // An array of conditions that define which members of the related time series are // transformed. TimeSeriesConditions []TimeSeriesCondition noSmithyDocumentSerde } // The weighted loss value for a quantile. This object is part of the Metrics // object. type WeightedQuantileLoss struct { // The difference between the predicted value and the actual value over the // quantile, weighted (normalized) by dividing by the sum over all quantiles. LossValue *float64 // The quantile. Quantiles divide a probability distribution into regions of equal // probability. For example, if the distribution was divided into 5 regions of // equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8. Quantile *float64 noSmithyDocumentSerde } // Provides a summary of the what-if analysis properties used in the // ListWhatIfAnalyses operation. To get the complete set of properties, call the // DescribeWhatIfAnalysis operation, and provide the WhatIfAnalysisArn that is // listed in the summary. type WhatIfAnalysisSummary struct { // When the what-if analysis was created. CreationTime *time.Time // The Amazon Resource Name (ARN) of the baseline forecast that is being used in // this what-if analysis. ForecastArn *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 what-if analysis. States include: // - ACTIVE // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - CREATE_STOPPING , CREATE_STOPPED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED // The Status of the what-if analysis must be ACTIVE before you can access the // analysis. Status *string // The Amazon Resource Name (ARN) of the what-if analysis. WhatIfAnalysisArn *string // The name of the what-if analysis. WhatIfAnalysisName *string noSmithyDocumentSerde } // Provides a summary of the what-if forecast export properties used in the // ListWhatIfForecastExports operation. To get the complete set of properties, call // the DescribeWhatIfForecastExport operation, and provide the // WhatIfForecastExportArn that is listed in the summary. type WhatIfForecastExportSummary struct { // When the what-if forecast export was created. CreationTime *time.Time // The path to the Amazon Simple Storage Service (Amazon S3) bucket where the // forecast is exported. Destination *DataDestination // 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 what-if forecast export. States include: // - ACTIVE // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - CREATE_STOPPING , CREATE_STOPPED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED // The Status of the what-if analysis must be ACTIVE before you can access the // analysis. Status *string // An array of Amazon Resource Names (ARNs) that define the what-if forecasts // included in the export. WhatIfForecastArns []string // The Amazon Resource Name (ARN) of the what-if forecast export. WhatIfForecastExportArn *string // The what-if forecast export name. WhatIfForecastExportName *string noSmithyDocumentSerde } // Provides a summary of the what-if forecast properties used in the // ListWhatIfForecasts operation. To get the complete set of properties, call the // DescribeWhatIfForecast operation, and provide the WhatIfForecastArn that is // listed in the summary. type WhatIfForecastSummary struct { // When the what-if forecast was created. CreationTime *time.Time // 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 what-if forecast. States include: // - ACTIVE // - CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED // - CREATE_STOPPING , CREATE_STOPPED // - DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED // The Status of the what-if analysis must be ACTIVE before you can access the // analysis. Status *string // The Amazon Resource Name (ARN) of the what-if analysis that contains this // what-if forecast. WhatIfAnalysisArn *string // The Amazon Resource Name (ARN) of the what-if forecast. WhatIfForecastArn *string // The name of the what-if forecast. WhatIfForecastName *string noSmithyDocumentSerde } // The metrics for a time range within the evaluation portion of a dataset. This // object is part of the EvaluationResult object. The TestWindowStart and // TestWindowEnd parameters are determined by the BackTestWindowOffset parameter // of the EvaluationParameters object. type WindowSummary struct { // The type of evaluation. // - SUMMARY - The average metrics across all windows. // - COMPUTED - The metrics for the specified window. EvaluationType EvaluationType // The number of data points within the window. ItemCount *int32 // Provides metrics used to evaluate the performance of a predictor. Metrics *Metrics // The timestamp that defines the end of the window. TestWindowEnd *time.Time // The timestamp that defines the start of the window. TestWindowStart *time.Time noSmithyDocumentSerde } type noSmithyDocumentSerde = smithydocument.NoSerde