[−][src]Struct rusoto_forecast::HyperParameterTuningJobConfig
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[src]
pub fn clone(&self) -> HyperParameterTuningJobConfig[src]
pub fn clone_from(&mut self, source: &Self)1.0.0[src]
impl Debug for HyperParameterTuningJobConfig[src]
impl Default for HyperParameterTuningJobConfig[src]
pub fn default() -> HyperParameterTuningJobConfig[src]
impl<'de> Deserialize<'de> for HyperParameterTuningJobConfig[src]
pub fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>, [src]
__D: Deserializer<'de>,
impl PartialEq<HyperParameterTuningJobConfig> for HyperParameterTuningJobConfig[src]
pub fn eq(&self, other: &HyperParameterTuningJobConfig) -> bool[src]
pub fn ne(&self, other: &HyperParameterTuningJobConfig) -> bool[src]
impl Serialize for HyperParameterTuningJobConfig[src]
pub fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
__S: Serializer, [src]
__S: Serializer,
impl StructuralPartialEq for HyperParameterTuningJobConfig[src]
Auto Trait Implementations
impl RefUnwindSafe for HyperParameterTuningJobConfig[src]
impl Send for HyperParameterTuningJobConfig[src]
impl Sync for HyperParameterTuningJobConfig[src]
impl Unpin for HyperParameterTuningJobConfig[src]
impl UnwindSafe for HyperParameterTuningJobConfig[src]
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized, [src]
T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized, [src]
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized, [src]
T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T[src]
impl<T> DeserializeOwned for T where
T: for<'de> Deserialize<'de>, [src]
T: for<'de> Deserialize<'de>,
impl<T> From<T> for T[src]
impl<T> Instrument for T[src]
pub fn instrument(self, span: Span) -> Instrumented<Self>[src]
pub fn in_current_span(self) -> Instrumented<Self>[src]
impl<T> Instrument for T[src]
pub fn instrument(self, span: Span) -> Instrumented<Self>[src]
pub fn in_current_span(self) -> Instrumented<Self>[src]
impl<T, U> Into<U> for T where
U: From<T>, [src]
U: From<T>,
impl<T> Same<T> for T
type Output = T
Should always be Self
impl<T> ToOwned for T where
T: Clone, [src]
T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T[src]
pub fn clone_into(&self, target: &mut T)[src]
impl<T, U> TryFrom<U> for T where
U: Into<T>, [src]
U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>[src]
impl<T, U> TryInto<U> for T where
U: TryFrom<T>, [src]
U: TryFrom<T>,