Struct DecisionTreeConfig

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pub struct DecisionTreeConfig {Show 16 fields
    pub criterion: SplitCriterion,
    pub max_depth: Option<usize>,
    pub min_samples_split: usize,
    pub min_samples_leaf: usize,
    pub max_features: MaxFeatures,
    pub random_state: Option<u64>,
    pub min_weight_fraction_leaf: f64,
    pub min_impurity_decrease: f64,
    pub pruning: PruningStrategy,
    pub missing_values: MissingValueStrategy,
    pub feature_types: Option<Vec<FeatureType>>,
    pub growing_strategy: TreeGrowingStrategy,
    pub split_type: SplitType,
    pub monotonic_constraints: Option<Vec<MonotonicConstraint>>,
    pub interaction_constraints: InteractionConstraint,
    pub feature_grouping: FeatureGrouping,
}

Expand description

Configuration for Decision Trees

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§criterion: SplitCriterion

Split criterion

§max_depth: Option<usize>

Maximum depth of the tree

§min_samples_split: usize

Minimum samples required to split an internal node

§min_samples_leaf: usize

Minimum samples required to be at a leaf node

§max_features: MaxFeatures

Maximum number of features to consider for splits

§random_state: Option<u64>

Random seed for reproducibility

§min_weight_fraction_leaf: f64

Minimum weighted fraction of samples required to be at a leaf

§min_impurity_decrease: f64

Minimum impurity decrease required for a split

§pruning: PruningStrategy

Pruning strategy to apply

§missing_values: MissingValueStrategy

Strategy for handling missing values

§feature_types: Option<Vec<FeatureType>>

Feature types for each feature (enables multiway splits for categorical features)

§growing_strategy: TreeGrowingStrategy

Tree growing strategy

§split_type: SplitType

Split type (axis-aligned or oblique)

§monotonic_constraints: Option<Vec<MonotonicConstraint>>

Monotonic constraints for each feature

§interaction_constraints: InteractionConstraint

Interaction constraints between features

§feature_grouping: FeatureGrouping

Feature grouping strategy for handling correlated features

Trait Implementations§

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impl Clone for DecisionTreeConfig

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fn clone(&self) -> DecisionTreeConfig

Returns a duplicate of the value. Read more

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

Performs copy-assignment from source. Read more

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impl Debug for DecisionTreeConfig

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

Formats the value using the given formatter. Read more

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impl Default for DecisionTreeConfig

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fn default() -> Self

Returns the “default value” for a type. Read more

Auto Trait Implementations§

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impl UnwindSafe for DecisionTreeConfig

Blanket Implementations§

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impl<T> Any for T
where T: 'static + ?Sized,

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

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impl<T> BorrowMut<T> for T
where T: ?Sized,

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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

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impl<T> CloneToUninit for T
where T: Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)

Performs copy-assignment from self to dest. Read more

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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into for T
where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T> IntoEither for T

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fn into_either(self, into_left: bool) -> Either<Self, Self>

Converts self into a Left variant of Either<Self, Self> if into_left is true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more

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fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

Converts self into a Left variant of Either<Self, Self> if into_left(&self) returns true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more

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