Struct DecisionTree 

pub struct DecisionTree<T, F>
where
    T: Clone + PartialOrd + Debug + ToPrimitive,
    F: Float,
{ /* private fields */ }

Decision tree for regression and classification tasks with support for generic data types

Type parameters:

• T - The type of the input features and target values (e.g., i32, u32, f64, or any custom type)
• F - The floating-point type used for internal calculations (typically f32 or f64)

Implementations

impl<T, F> DecisionTree<T, F>

where T: Clone + PartialOrd + Eq + Hash + Send + Sync + NumCast + ToPrimitive + Debug + AsPrimitive<F>, F: Float + Send + Sync + NumCast + FromPrimitive + 'static + AsPrimitive<T>, f64: AsPrimitive<F>, usize: AsPrimitive<F>,

pub fn new( tree_type: TreeType, criterion: SplitCriterion, max_depth: usize, min_samples_split: usize, min_samples_leaf: usize, ) -> Self

Create a new decision tree

pub fn fit<D>(&mut self, features: &[Vec<D>], target: &[T]) -> StatsResult<()>

where D: Clone + PartialOrd + NumCast + ToPrimitive + AsPrimitive<F> + Send + Sync, T: FromPrimitive,

Train the decision tree on the given data

Errors

Returns StatsError::EmptyData if features or target arrays are empty. Returns StatsError::DimensionMismatch if features and target have different lengths. Returns StatsError::InvalidInput if feature vectors have inconsistent lengths. Returns StatsError::ConversionError if value conversion fails.

pub fn predict<D>(&self, features: &[Vec<D>]) -> StatsResult<Vec<T>>

where D: Clone + PartialOrd + NumCast, T: NumCast,

Make predictions for new data

Errors

Returns StatsError::NotFitted if the tree has not been trained. Returns StatsError::ConversionError if value conversion fails.

pub fn feature_importances(&self) -> Vec<F>

Get the importance of each feature

pub fn tree_structure(&self) -> String

Get a textual representation of the tree structure

impl<T, F> DecisionTree<T, F>

where T: Clone + PartialOrd + Eq + Hash + Send + Sync + NumCast + ToPrimitive + Debug + AsPrimitive<F>, F: Float + Send + Sync + NumCast + FromPrimitive + 'static + AsPrimitive<T>, f64: AsPrimitive<F>, usize: AsPrimitive<F>,

Implementation of additional methods for enhanced usability

pub fn get_max_depth(&self) -> usize

Get the maximum depth of the tree

pub fn get_node_count(&self) -> usize

Get the number of nodes in the tree

pub fn is_trained(&self) -> bool

Check if the tree has been trained

pub fn get_leaf_count(&self) -> usize

Get the number of leaf nodes in the tree

pub fn calculate_depth(&self) -> usize

Calculate the actual depth of the tree

pub fn summary(&self) -> String

Print a summary of the tree

Trait Implementations

impl<T, F> Clone for DecisionTree<T, F>

where T: Clone + PartialOrd + Debug + ToPrimitive + Clone, F: Float + Clone,

fn clone(&self) -> DecisionTree<T, F>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T, F> Debug for DecisionTree<T, F>

where T: Clone + PartialOrd + Debug + ToPrimitive + Debug, F: Float + Debug,

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

Formats the value using the given formatter.

impl<T, F> Display for DecisionTree<T, F>

where T: Clone + PartialOrd + Eq + Hash + Debug + ToPrimitive, F: Float,

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

Formats the value using the given formatter.