Struct DecisionTreeRegressor 

pub struct DecisionTreeRegressor { /* private fields */ }

Decision tree regressor using the CART algorithm.

Uses Mean Squared Error (MSE) for splitting criterion and builds trees recursively. Leaf nodes predict the mean of target values.

Implementations

impl DecisionTreeRegressor

pub fn new() -> Self

Creates a new decision tree regressor with default parameters.

pub fn with_max_depth(self, depth: usize) -> Self

Sets the maximum depth of the tree.

Arguments

• depth - Maximum depth (root has depth 0)

pub fn with_min_samples_split(self, min_samples: usize) -> Self

Sets the minimum number of samples required to split an internal node.

Arguments

• min_samples - Minimum samples to split (must be >= 2)

pub fn with_min_samples_leaf(self, min_samples: usize) -> Self

Sets the minimum number of samples required to be at a leaf node.

Arguments

• min_samples - Minimum samples per leaf (must be >= 1)

pub fn fit(&mut self, x: &Matrix<f32>, y: &Vector<f32>) -> Result<()>

Fits the decision tree to training data.

Arguments

• x - Training features (n_samples × n_features)
• y - Training target values (n_samples continuous values)

Errors

Returns an error if the data is invalid.

pub fn predict(&self, x: &Matrix<f32>) -> Vector<f32>

Predicts target values for samples.

Arguments

• x - Feature matrix (n_samples × n_features)

Returns

Vector of predicted values

Panics

Panics if called before fit()

pub fn score(&self, x: &Matrix<f32>, y: &Vector<f32>) -> f32

Computes the R² score on test data.

Arguments

• x - Test features (n_samples × n_features)
• y - True target values (n_samples)

Returns

R² coefficient of determination

Trait Implementations

impl Clone for DecisionTreeRegressor

fn clone(&self) -> DecisionTreeRegressor

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for DecisionTreeRegressor

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

Formats the value using the given formatter.

impl Default for DecisionTreeRegressor

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for DecisionTreeRegressor

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for DecisionTreeRegressor

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.