Struct RandomForestRegressor 

#[non_exhaustive]
pub struct RandomForestRegressor { /* private fields */ }

Random Forest for regression (mean of tree predictions).

Implementations

impl RandomForestRegressor

pub fn new() -> Self

Create a new regressor forest.

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

Set number of trees.

pub fn max_depth(self, d: usize) -> Self

Set maximum depth.

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

Set feature selection strategy.

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

Set random seed.

pub fn fit(&mut self, data: &Dataset) -> Result<()>

Train the forest.

pub fn predict(&self, features: &[Vec<f64>]) -> Result<Vec<f64>>

Predict values (mean across trees).

Parallelized across samples via rayon.

pub fn feature_importances(&self) -> Result<Vec<f64>>

Feature importances.

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

Get individual trees (for inspection or ONNX export).

pub fn n_features(&self) -> usize

Number of features the model was trained on.

Trait Implementations

impl Clone for RandomForestRegressor

fn clone(&self) -> RandomForestRegressor

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Default for RandomForestRegressor

fn default() -> Self

Returns the “default value” for a type.

impl PipelineModel for RandomForestRegressor

fn fit(&mut self, data: &Dataset) -> Result<()>

Train the model on a dataset.

fn predict(&self, features: &[Vec<f64>]) -> Result<Vec<f64>>

Predict on row-major feature matrix.