MetaLearningStrategy

Enum MetaLearningStrategy 

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pub enum MetaLearningStrategy {
    SimilarityBased {
        similarity_metric: SimilarityMetric,
        k_neighbors: usize,
        weight_by_distance: bool,
    },
    ModelBased {
        surrogate_model: SurrogateModel,
        update_frequency: usize,
    },
    GradientBased {
        meta_learning_rate: Float,
        adaptation_steps: usize,
        inner_learning_rate: Float,
    },
    BayesianMeta {
        prior_strength: Float,
        hierarchical_levels: usize,
    },
    TransferLearning {
        transfer_method: TransferMethod,
        domain_adaptation: bool,
    },
    EnsembleMeta {
        strategies: Vec<MetaLearningStrategy>,
        combination_method: CombinationMethod,
    },
}
Expand description

Meta-learning strategies for hyperparameter initialization

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SimilarityBased

Similarity-based recommendation using dataset characteristics

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§similarity_metric: SimilarityMetric
§k_neighbors: usize
§weight_by_distance: bool
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ModelBased

Model-based meta-learning using surrogate models

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§surrogate_model: SurrogateModel
§update_frequency: usize
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GradientBased

Gradient-based meta-learning (MAML-style)

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§meta_learning_rate: Float
§adaptation_steps: usize
§inner_learning_rate: Float
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BayesianMeta

Bayesian meta-learning using hierarchical models

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§prior_strength: Float
§hierarchical_levels: usize
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TransferLearning

Transfer learning from similar tasks

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§transfer_method: TransferMethod
§domain_adaptation: bool
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EnsembleMeta

Ensemble of meta-learners

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§combination_method: CombinationMethod

Trait Implementations§

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impl Clone for MetaLearningStrategy

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fn clone(&self) -> MetaLearningStrategy

Returns a duplicate of the value. Read more
1.0.0 · Source§

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

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

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

Formats the value using the given formatter. Read more

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🔬This is a nightly-only experimental API. (clone_to_uninit)
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