Struct GradientBoostingClassifier 

pub struct GradientBoostingClassifier { /* private fields */ }

Gradient boosting for 0/1 classification (log loss). Defaults match scikit-learn’s GradientBoostingClassifier.

Implementations

impl GradientBoostingClassifier

pub fn new() -> Self

pub fn n_estimators(self, n: usize) -> Self

Number of boosting stages (default 100).

pub fn learning_rate(self, rate: f64) -> Self

Shrinkage applied to every tree (default 0.1). Smaller values need more stages but usually generalise better.

pub fn max_depth(self, depth: Option<usize>) -> Self

Maximum depth of each tree (default 3); None for unlimited.

pub fn min_samples_split(self, n: usize) -> Self

Minimum number of rows to split a node (default 2).

pub fn min_samples_leaf(self, n: usize) -> Self

Minimum number of rows in each leaf (default 1).

pub fn max_features(self, m: MaxFeatures) -> Self

Features considered per split (default: all).

pub fn subsample(self, fraction: f64) -> Self

Fraction of rows drawn (without replacement) for each stage (default 1.0); below 1 gives stochastic gradient boosting.

pub fn seed(self, seed: u64) -> Self

Seed for row subsampling and feature subsets (default 0).

pub fn feature_importances(&self) -> Option<&Array1<f64>>

Total impurity reduction per feature over all trees (sums to one).

pub fn n_trees(&self) -> usize

Number of fitted trees.

Trait Implementations

impl Classifier for GradientBoostingClassifier

fn fit(&mut self, x: ArrayView2<'_, f64>, y: ArrayView1<'_, f64>) -> Result<()>

fn predict_proba(&self, x: ArrayView2<'_, f64>) -> Result<Array1<f64>>

fn fresh(&self) -> Box<dyn Classifier>

impl Clone for GradientBoostingClassifier

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GradientBoostingClassifier

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

Formats the value using the given formatter.

impl Default for GradientBoostingClassifier

fn default() -> Self

Returns the “default value” for a type.