Struct aws_sdk_forecast::model::ExplainabilityConfig

#[non_exhaustive]
pub struct ExplainabilityConfig {
    pub time_series_granularity: Option<TimeSeriesGranularity>,
    pub time_point_granularity: Option<TimePointGranularity>,
}

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”.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

time_series_granularity: Option<TimeSeriesGranularity>

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 file to an Amazon S3 bucket and set the location within the DataDestination data type.

time_point_granularity: Option<TimePointGranularity>

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.

Implementations

impl ExplainabilityConfig

pub fn time_series_granularity(&self) -> Option<&TimeSeriesGranularity>

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 file to an Amazon S3 bucket and set the location within the DataDestination data type.

pub fn time_point_granularity(&self) -> Option<&TimePointGranularity>

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.

impl ExplainabilityConfig

pub fn builder() -> Builder

Creates a new builder-style object to manufacture ExplainabilityConfig

Trait Implementations

impl Clone for ExplainabilityConfig

fn clone(&self) -> ExplainabilityConfig

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ExplainabilityConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq<ExplainabilityConfig> for ExplainabilityConfig

fn eq(&self, other: &ExplainabilityConfig) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &ExplainabilityConfig) -> bool

This method tests for !=.

impl StructuralPartialEq for ExplainabilityConfig