#[non_exhaustive]
pub struct CandidateGenerationConfig { pub algorithms_config: Option<Vec<AutoMlAlgorithmConfig>>, }
Expand description

Stores the configuration information for how model candidates are generated using an AutoML job V2.

Fields (Non-exhaustive)§

This struct is marked as 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.
§algorithms_config: Option<Vec<AutoMlAlgorithmConfig>>

Stores the configuration information for the selection of algorithms used to train model candidates on tabular data.

The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode .

  • AlgorithmsConfig should not be set in AUTO training mode.

  • When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.

    If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

  • When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.

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impl CandidateGenerationConfig

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pub fn algorithms_config(&self) -> &[AutoMlAlgorithmConfig]

Stores the configuration information for the selection of algorithms used to train model candidates on tabular data.

The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode .

  • AlgorithmsConfig should not be set in AUTO training mode.

  • When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.

    If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

  • When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.

For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.

For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .algorithms_config.is_none().

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impl CandidateGenerationConfig

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pub fn builder() -> CandidateGenerationConfigBuilder

Creates a new builder-style object to manufacture CandidateGenerationConfig.

Trait Implementations§

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impl Clone for CandidateGenerationConfig

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fn clone(&self) -> CandidateGenerationConfig

Returns a copy of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for CandidateGenerationConfig

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

Formats the value using the given formatter. Read more
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impl PartialEq for CandidateGenerationConfig

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

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

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type Error = Infallible

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type Error = <U as TryFrom<T>>::Error

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