Struct EnsembleAnalyzer 

pub struct EnsembleAnalyzer {
    pub importance_method: ImportanceAggregationMethod,
    pub random_state: Option<u64>,
    pub n_bootstrap: usize,
    pub confidence_level: Float,
}

Ensemble analyzer for feature importance and uncertainty quantification

Fields

importance_method: ImportanceAggregationMethod

Method for aggregating feature importances

random_state: Option<u64>

Random state for reproducible analysis

n_bootstrap: usize

Number of bootstrap samples for confidence intervals

confidence_level: Float

Confidence level for intervals

Implementations

impl EnsembleAnalyzer

pub fn new(importance_method: ImportanceAggregationMethod) -> Self

Create a new ensemble analyzer

pub fn with_bootstrap(self, n_bootstrap: usize, confidence_level: Float) -> Self

Configure bootstrap parameters

pub fn with_random_state(self, random_state: u64) -> Self

Set random state for reproducible results

pub fn analyze_feature_importance( &self, individual_importances: &Array2<Float>, model_weights: Option<&Array1<Float>>, ) -> Result<FeatureImportanceAnalysis>

Analyze feature importances across ensemble models

pub fn quantify_uncertainty( &self, ensemble_predictions: &Array2<Float>, true_labels: Option<&Array1<Float>>, ) -> Result<UncertaintyQuantification>

Quantify uncertainty in ensemble predictions

impl EnsembleAnalyzer

Convenience functions for common analysis tasks

pub fn mean_importance() -> Self

Create analyzer for mean-based feature importance aggregation

pub fn weighted_importance(weights: Vec<Float>) -> Self

Create analyzer for weighted feature importance aggregation

pub fn robust_importance() -> Self

Create analyzer for robust median-based aggregation

pub fn rank_based_importance() -> Self

Create analyzer for rank-based aggregation

pub fn permutation_importance(n_repeats: usize) -> Self

Create analyzer with permutation-based importance

pub fn shap_importance(background_samples: usize) -> Self

Create analyzer with SHAP-based importance

Trait Implementations

impl Default for EnsembleAnalyzer

fn default() -> Self

Returns the “default value” for a type.