Struct DecisionTreeClassifier 

pub struct DecisionTreeClassifier {
    pub max_depth: Option<usize>,
    pub min_samples_split: usize,
    pub min_samples_leaf: usize,
    pub max_features: Option<usize>,
    pub criterion: Criterion,
    /* private fields */
}

Decision Tree Classifier using CART algorithm

Fields

max_depth: Option<usize>

Maximum depth of tree

min_samples_split: usize

Minimum samples to split

min_samples_leaf: usize

Minimum samples in leaf

max_features: Option<usize>

Maximum features to consider

criterion: Criterion

Split criterion

Implementations

impl DecisionTreeClassifier

pub fn new() -> Self

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

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

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

pub fn criterion(self, criterion: Criterion) -> Self

pub fn fit(&mut self, x: &Tensor, y: &Tensor)

Fit the decision tree

pub fn predict(&self, x: &Tensor) -> Tensor

Predict class labels

pub fn predict_proba(&self, x: &Tensor) -> Tensor

Predict class probabilities

Trait Implementations

impl Default for DecisionTreeClassifier

fn default() -> Self

Returns the “default value” for a type.