Struct FittedRandomTreesEmbedding 

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

A fitted random trees embedding.

Stores the ensemble of randomly built trees. Each tree’s leaves are enumerated, and Transform produces a one-hot encoded matrix of shape (n_samples, total_leaves).

Implementations

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

pub fn n_estimators(&self) -> usize

Returns the number of trees in the ensemble.

pub fn n_features(&self) -> usize

Returns the number of features the model was trained on.

pub fn n_output_features(&self) -> usize

Returns the total number of output features (total leaves across all trees).

Trait Implementations

impl<F: Clone> Clone for FittedRandomTreesEmbedding<F>

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F: Debug> Debug for FittedRandomTreesEmbedding<F>

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

Formats the value using the given formatter.

impl<F: Float + Send + Sync + 'static> FittedPipelineTransformer<F> for FittedRandomTreesEmbedding<F>

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

Transform the input data.

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

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

Transform the input data into a one-hot encoded leaf-index representation.

For each sample, traverse each tree to a leaf node, then one-hot encode the leaf index within that tree. The encodings for all trees are concatenated horizontally to produce the output.

Output shape: (n_samples, total_leaves_across_all_trees).

Errors

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

type Output = ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>

The transformed output type.

type Error = FerroError

The error type returned by transform.