Struct aws_sdk_sagemaker::types::AutoMlJobObjective

#[non_exhaustive]
pub struct AutoMlJobObjective {
    pub metric_name: Option<AutoMlMetricEnum>,
}

Specifies a metric to minimize or maximize as the objective of a job.

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.

metric_name: Option<AutoMlMetricEnum>

The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.

For the list of all available metrics supported by Autopilot, see Autopilot metrics.

If you do not specify a metric explicitly, the default behavior is to automatically use:

• For tabular problem types:

  • Regression: MSE.

  • Binary classification: F1.

  • Multiclass classification: Accuracy.

• For image or text classification problem types: Accuracy

• For time-series forecasting problem types: AverageWeightedQuantileLoss

Implementations

impl AutoMlJobObjective

pub fn metric_name(&self) -> Option<&AutoMlMetricEnum>

The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.

For the list of all available metrics supported by Autopilot, see Autopilot metrics.

If you do not specify a metric explicitly, the default behavior is to automatically use:

• For tabular problem types:

  • Regression: MSE.

  • Binary classification: F1.

  • Multiclass classification: Accuracy.

• For image or text classification problem types: Accuracy

• For time-series forecasting problem types: AverageWeightedQuantileLoss

impl AutoMlJobObjective

pub fn builder() -> AutoMlJobObjectiveBuilder

Creates a new builder-style object to manufacture AutoMlJobObjective.

Trait Implementations

impl Clone for AutoMlJobObjective

fn clone(&self) -> AutoMlJobObjective

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for AutoMlJobObjective

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

Formats the value using the given formatter.

impl PartialEq for AutoMlJobObjective

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

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

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

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for AutoMlJobObjective