pub enum Algorithm {
ID3,
C45,
CART,
}Expand description
Represents different decision tree algorithms that can be used for tree construction.
§Variants
ID3- Iterative Dichotomiser 3 algorithm, which uses information gain for feature selection. Works best with categorical features.C45- An extension of ID3 that handles both continuous and discrete attributes, uses gain ratio instead of information gain to reduce bias towards features with many values.CART- Classification And Regression Trees algorithm, which builds binary trees using the feature and threshold that yield the largest information gain at each node. Works with both classification and regression problems.
Variants§
Trait Implementations§
impl StructuralPartialEq for Algorithm
Auto Trait Implementations§
impl Freeze for Algorithm
impl RefUnwindSafe for Algorithm
impl Send for Algorithm
impl Sync for Algorithm
impl Unpin for Algorithm
impl UnwindSafe for Algorithm
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more