Struct SolutionConfigBuilder

#[non_exhaustive]
pub struct SolutionConfigBuilder { /* private fields */ }

A builder for SolutionConfig.

Implementations

impl SolutionConfigBuilder

pub fn event_value_threshold(self, input: impl Into<String>) -> Self

Only events with a value greater than or equal to this threshold are used for training a model.

pub fn set_event_value_threshold(self, input: Option<String>) -> Self

Only events with a value greater than or equal to this threshold are used for training a model.

pub fn get_event_value_threshold(&self) -> &Option<String>

Only events with a value greater than or equal to this threshold are used for training a model.

pub fn hpo_config(self, input: HpoConfig) -> Self

Describes the properties for hyperparameter optimization (HPO).

pub fn set_hpo_config(self, input: Option<HpoConfig>) -> Self

Describes the properties for hyperparameter optimization (HPO).

pub fn get_hpo_config(&self) -> &Option<HpoConfig>

Describes the properties for hyperparameter optimization (HPO).

pub fn algorithm_hyper_parameters( self, k: impl Into<String>, v: impl Into<String>, ) -> Self

Adds a key-value pair to algorithm_hyper_parameters.

To override the contents of this collection use set_algorithm_hyper_parameters.

Lists the algorithm hyperparameters and their values.

pub fn set_algorithm_hyper_parameters( self, input: Option<HashMap<String, String>>, ) -> Self

Lists the algorithm hyperparameters and their values.

pub fn get_algorithm_hyper_parameters(&self) -> &Option<HashMap<String, String>>

Lists the algorithm hyperparameters and their values.

pub fn feature_transformation_parameters( self, k: impl Into<String>, v: impl Into<String>, ) -> Self

Adds a key-value pair to feature_transformation_parameters.

To override the contents of this collection use set_feature_transformation_parameters.

Lists the feature transformation parameters.

pub fn set_feature_transformation_parameters( self, input: Option<HashMap<String, String>>, ) -> Self

Lists the feature transformation parameters.

pub fn get_feature_transformation_parameters( &self, ) -> &Option<HashMap<String, String>>

Lists the feature transformation parameters.

pub fn auto_ml_config(self, input: AutoMlConfig) -> Self

The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

pub fn set_auto_ml_config(self, input: Option<AutoMlConfig>) -> Self

The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

pub fn get_auto_ml_config(&self) -> &Option<AutoMlConfig>

The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

pub fn events_config(self, input: EventsConfig) -> Self

Describes the configuration of an event, which includes a list of event parameters. You can specify up to 10 event parameters. Events are used in solution creation.

pub fn set_events_config(self, input: Option<EventsConfig>) -> Self

Describes the configuration of an event, which includes a list of event parameters. You can specify up to 10 event parameters. Events are used in solution creation.

pub fn get_events_config(&self) -> &Option<EventsConfig>

Describes the configuration of an event, which includes a list of event parameters. You can specify up to 10 event parameters. Events are used in solution creation.

pub fn optimization_objective(self, input: OptimizationObjective) -> Self

Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

pub fn set_optimization_objective( self, input: Option<OptimizationObjective>, ) -> Self

Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

pub fn get_optimization_objective(&self) -> &Option<OptimizationObjective>

Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

pub fn training_data_config(self, input: TrainingDataConfig) -> Self

Specifies the training data configuration to use when creating a custom solution version (trained model).

pub fn set_training_data_config(self, input: Option<TrainingDataConfig>) -> Self

Specifies the training data configuration to use when creating a custom solution version (trained model).

pub fn get_training_data_config(&self) -> &Option<TrainingDataConfig>

Specifies the training data configuration to use when creating a custom solution version (trained model).

pub fn auto_training_config(self, input: AutoTrainingConfig) -> Self

Specifies the automatic training configuration to use.

pub fn set_auto_training_config(self, input: Option<AutoTrainingConfig>) -> Self

Specifies the automatic training configuration to use.

pub fn get_auto_training_config(&self) -> &Option<AutoTrainingConfig>

Specifies the automatic training configuration to use.

pub fn build(self) -> SolutionConfig

Consumes the builder and constructs a SolutionConfig.

Trait Implementations

impl Clone for SolutionConfigBuilder

fn clone(&self) -> SolutionConfigBuilder

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SolutionConfigBuilder

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

Formats the value using the given formatter.

impl Default for SolutionConfigBuilder

fn default() -> SolutionConfigBuilder

Returns the “default value” for a type.

impl PartialEq for SolutionConfigBuilder

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for SolutionConfigBuilder