Struct FittedRandomForestClassifier 

pub struct FittedRandomForestClassifier<F> { /* private fields */ }

A fitted random forest classifier.

Stores the ensemble of fitted decision trees and aggregates their predictions by majority vote.

Implementations

impl<F: Float + Send + Sync + 'static> FittedRandomForestClassifier<F>

pub fn trees(&self) -> &[Vec<Node<F>>]

Returns a reference to the individual tree node vectors.

pub fn n_features(&self) -> usize

Returns the number of features the model was trained on.

pub fn score(&self, x: &Array2<F>, y: &Array1<usize>) -> Result<F, FerroError>

Mean accuracy on the given test data and labels. Equivalent to sklearn’s ClassifierMixin.score.

Errors

Returns FerroError::ShapeMismatch if x.nrows() != y.len() or the feature count does not match the training data.

pub fn predict_proba(&self, x: &Array2<F>) -> Result<Array2<F>, FerroError>

Predict class probabilities for each sample by averaging per-tree class distributions across the forest. Equivalent to sklearn’s RandomForestClassifier.predict_proba.

Returns an (n_samples, n_classes) array. Each row sums to 1. When a leaf does not carry a class distribution, it contributes a one-hot vote at the leaf’s predicted class.

Errors

Returns FerroError::ShapeMismatch if the number of features does not match the training data.

pub fn predict_log_proba(&self, x: &Array2<F>) -> Result<Array2<F>, FerroError>

Element-wise log of predict_proba. Mirrors sklearn’s ClassifierMixin.predict_log_proba.

Errors

Forwards any error from predict_proba.

Trait Implementations

impl<F: Clone> Clone for FittedRandomForestClassifier<F>

fn clone(&self) -> FittedRandomForestClassifier<F>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F: Debug> Debug for FittedRandomForestClassifier<F>

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

Formats the value using the given formatter.

impl<F: Float + Send + Sync + 'static> HasClasses for FittedRandomForestClassifier<F>

fn classes(&self) -> &[usize]

Returns the sorted list of unique class labels.

fn n_classes(&self) -> usize

Returns the number of distinct classes.

impl<F: Float + Send + Sync + 'static> HasFeatureImportances<F> for FittedRandomForestClassifier<F>

fn feature_importances(&self) -> &Array1<F>

Returns a reference to the feature importance array.

impl<F: Float + Send + Sync + 'static> Predict<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for FittedRandomForestClassifier<F>

fn predict(&self, x: &Array2<F>) -> Result<Array1<usize>, FerroError>

Predict class labels by majority vote across all trees.

Errors

Returns FerroError::ShapeMismatch if the number of features does not match the fitted model.

type Output = ArrayBase<OwnedRepr<usize>, Dim<[usize; 1]>>

The prediction output type (e.g., ndarray::Array1<F> or ndarray::Array1<usize>).

type Error = FerroError

The error type returned by predict.