Skip to content

Create Explainability

forecastservice_create_explainability R Documentation

Explainability is only available for Forecasts and Predictors generated from an AutoPredictor (CreateAutoPredictor)

Description

Explainability is only available for Forecasts and Predictors generated from an AutoPredictor (create_auto_predictor)

Creates an Amazon Forecast Explainability.

Explainability helps you better understand how the attributes in your datasets impact forecast. Amazon Forecast uses a metric called Impact scores to quantify the relative impact of each attribute and determine whether they increase or decrease forecast values.

To enable Forecast Explainability, your predictor must include at least one of the following: related time series, item metadata, or additional datasets like Holidays and the Weather Index.

CreateExplainability accepts either a Predictor ARN or Forecast ARN. To receive aggregated Impact scores for all time series and time points in your datasets, provide a Predictor ARN. To receive Impact scores for specific time series and time points, provide a Forecast ARN.

CreateExplainability with a Predictor ARN

You can only have one Explainability resource per predictor. If you already enabled ExplainPredictor in create_auto_predictor, that predictor already has an Explainability resource.

The following parameters are required when providing a Predictor ARN:

  • ExplainabilityName - A unique name for the Explainability.

  • ResourceArn - The Arn of the predictor.

  • TimePointGranularity - Must be set to “ALL”.

  • TimeSeriesGranularity - Must be set to “ALL”.

Do not specify a value for the following parameters:

  • DataSource - Only valid when TimeSeriesGranularity is “SPECIFIC”.

  • Schema - Only valid when TimeSeriesGranularity is “SPECIFIC”.

  • StartDateTime - Only valid when TimePointGranularity is “SPECIFIC”.

  • EndDateTime - Only valid when TimePointGranularity is “SPECIFIC”.

CreateExplainability with a Forecast ARN

You can specify a maximum of 50 time series and 500 time points.

The following parameters are required when providing a Predictor ARN:

  • ExplainabilityName - A unique name for the Explainability.

  • ResourceArn - The Arn of the forecast.

  • TimePointGranularity - Either “ALL” or “SPECIFIC”.

  • TimeSeriesGranularity - Either “ALL” or “SPECIFIC”.

If you set TimeSeriesGranularity to “SPECIFIC”, you must also provide the following:

  • DataSource - The S3 location of the CSV file specifying your time series.

  • Schema - The Schema defines the attributes and attribute types listed in the Data Source.

If you set TimePointGranularity to “SPECIFIC”, you must also provide the following:

  • StartDateTime - The first timestamp in the range of time points.

  • EndDateTime - The last timestamp in the range of time points.

Usage

forecastservice_create_explainability(ExplainabilityName, ResourceArn,
  ExplainabilityConfig, DataSource, Schema, EnableVisualization,
  StartDateTime, EndDateTime, Tags)

Arguments

ExplainabilityName

[required] A unique name for the Explainability.
ResourceArn

[required] The Amazon Resource Name (ARN) of the Predictor or Forecast used to create the Explainability.
ExplainabilityConfig

[required] The configuration settings that define the granularity of time series and time points for the Explainability.
DataSource
Schema
EnableVisualization

Create an Explainability visualization that is viewable within the Amazon Web Services console.
StartDateTime

If TimePointGranularity is set to SPECIFIC, define the first point for the Explainability.

Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)
EndDateTime

If TimePointGranularity is set to SPECIFIC, define the last time point for the Explainability.

Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)
Tags

Optional metadata to help you categorize and organize your resources. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

The following restrictions apply to tags:

  • For each resource, each tag key must be unique and each tag key must have one value.

  • Maximum number of tags per resource: 50.

  • Maximum key length: 128 Unicode characters in UTF-8.

  • Maximum value length: 256 Unicode characters in UTF-8.

  • Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

  • Key prefixes cannot include any upper or lowercase combination of ⁠aws:⁠ or ⁠AWS:⁠. Values can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this prefix.

Value

A list with the following syntax:

list(
  ExplainabilityArn = "string"
)

Request syntax

svc$create_explainability(
  ExplainabilityName = "string",
  ResourceArn = "string",
  ExplainabilityConfig = list(
    TimeSeriesGranularity = "ALL"|"SPECIFIC",
    TimePointGranularity = "ALL"|"SPECIFIC"
  ),
  DataSource = list(
    S3Config = list(
      Path = "string",
      RoleArn = "string",
      KMSKeyArn = "string"
    )
  ),
  Schema = list(
    Attributes = list(
      list(
        AttributeName = "string",
        AttributeType = "string"|"integer"|"float"|"timestamp"|"geolocation"
      )
    )
  ),
  EnableVisualization = TRUE|FALSE,
  StartDateTime = "string",
  EndDateTime = "string",
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)