Struct HyperParameterTuningJobConfig 

pub struct HyperParameterTuningJobConfig {
    pub parameter_ranges: Option<ParameterRanges>,
}

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.

Fields

parameter_ranges: Option<ParameterRanges>

Specifies the ranges of valid values for the hyperparameters.

Trait Implementations

impl Clone for HyperParameterTuningJobConfig

fn clone(&self) -> HyperParameterTuningJobConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for HyperParameterTuningJobConfig

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

Formats the value using the given formatter.

impl Default for HyperParameterTuningJobConfig

fn default() -> HyperParameterTuningJobConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for HyperParameterTuningJobConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for HyperParameterTuningJobConfig

fn eq(&self, other: &HyperParameterTuningJobConfig) -> 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 Serialize for HyperParameterTuningJobConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for HyperParameterTuningJobConfig