Struct GradientBoostedTrees 

pub struct GradientBoostedTrees { /* private fields */ }

Stage-wise gradient-boosted tree ensemble.

The ensemble keeps explicit tree weights and a base score so the semantic model can reconstruct raw margins exactly for both prediction and IR export.

Implementations

impl GradientBoostedTrees

pub fn new( task: Task, tree_type: TreeType, trees: Vec<Model>, tree_weights: Vec<f64>, base_score: f64, learning_rate: f64, bootstrap: bool, top_gradient_fraction: f64, other_gradient_fraction: f64, max_features: usize, seed: Option<u64>, num_features: usize, feature_preprocessing: Vec<FeaturePreprocessing>, class_labels: Option<Vec<f64>>, training_canaries: usize, ) -> Self

pub fn predict_table(&self, table: &dyn TableAccess) -> Vec<f64>

pub fn predict_proba_table( &self, table: &dyn TableAccess, ) -> Result<Vec<Vec<f64>>, PredictError>

pub fn task(&self) -> Task

pub fn criterion(&self) -> Criterion

pub fn tree_type(&self) -> TreeType

pub fn trees(&self) -> &[Model]

pub fn tree_weights(&self) -> &[f64]

pub fn base_score(&self) -> f64

pub fn num_features(&self) -> usize

pub fn feature_preprocessing(&self) -> &[FeaturePreprocessing]

pub fn class_labels(&self) -> Option<Vec<f64>>

pub fn training_metadata(&self) -> TrainingMetadata

Trait Implementations

impl Clone for GradientBoostedTrees

fn clone(&self) -> GradientBoostedTrees

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GradientBoostedTrees

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

Formats the value using the given formatter.