Struct DecisionTreeClassifier 

pub struct DecisionTreeClassifier {
    pub max_depth: Option<usize>,
    pub min_samples_split: usize,
    pub min_samples_leaf: usize,
    pub criterion: SplitCriterion,
    pub max_features: Option<MaxFeatures>,
    pub sample_weight: Option<Array1<f64>>,
    pub class_weight: Option<ClassWeight>,
}

Decision tree classifier parameters (unfitted state).

Fields

max_depth: Option<usize>

min_samples_split: usize

min_samples_leaf: usize

criterion: SplitCriterion

max_features: Option<MaxFeatures>

Maximum number of features to consider at each split.

sample_weight: Option<Array1<f64>>

Per-sample weights.

class_weight: Option<ClassWeight>

Class weighting strategy.

Implementations

impl DecisionTreeClassifier

pub fn new() -> Self

Create a new DecisionTreeClassifier with sensible defaults.

pub fn with_max_depth(self, max_depth: Option<usize>) -> Self

Set the maximum depth of the tree.

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

Set the minimum number of samples required to split a node.

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

Set the minimum number of samples required in a leaf node.

pub fn with_criterion(self, criterion: SplitCriterion) -> Self

Set the split quality criterion.

pub fn with_max_features(self, max_features: Option<MaxFeatures>) -> Self

Set the maximum number of features to consider at each split.

pub fn with_sample_weight(self, sample_weight: Option<Array1<f64>>) -> Self

Set per-sample weights.

pub fn with_class_weight(self, class_weight: Option<ClassWeight>) -> Self

Set class weighting strategy.

Trait Implementations

impl Clone for DecisionTreeClassifier

fn clone(&self) -> DecisionTreeClassifier

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for DecisionTreeClassifier

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

Formats the value using the given formatter.

impl Default for DecisionTreeClassifier

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for DecisionTreeClassifier

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<F: Float> Fit<F> for DecisionTreeClassifier

type Fitted = FittedDecisionTreeClassifier<F>

fn fit(&self, x: &Array2<F>, y: &Array1<F>) -> Result<Self::Fitted>

impl Serialize for DecisionTreeClassifier

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

where __S: Serializer,

Serialize this value into the given Serde serializer.