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Implement predict_proba for DecisionTreeClassifier (#287)

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* Implement predict_proba for DecisionTreeClassifier
* Some automated fixes suggested by cargo clippy --fix
This commit is contained in:
Lorenzo
2025-01-20 18:50:00 +00:00
committed by GitHub
parent 4523ac73ff
commit 3da433f757
13 changed files with 166 additions and 61 deletions
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src/linear/logistic_regression.rs
+4 -4
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@@ -258,8 +258,8 @@ impl<TX: Number + FloatNumber + RealNumber, TY: Number + Ord, X: Array2<TX>, Y:
}
}
impl<'a, T: Number + FloatNumber, X: Array2<T>> ObjectiveFunction<T, X>
for BinaryObjectiveFunction<'a, T, X>
impl<T: Number + FloatNumber, X: Array2<T>> ObjectiveFunction<T, X>
for BinaryObjectiveFunction<'_, T, X>
{
fn f(&self, w_bias: &[T]) -> T {
let mut f = T::zero();
@@ -313,8 +313,8 @@ struct MultiClassObjectiveFunction<'a, T: Number + FloatNumber, X: Array2<T>> {
_phantom_t: PhantomData<T>,
}
impl<'a, T: Number + FloatNumber + RealNumber, X: Array2<T>> ObjectiveFunction<T, X>
for MultiClassObjectiveFunction<'a, T, X>
impl<T: Number + FloatNumber + RealNumber, X: Array2<T>> ObjectiveFunction<T, X>
for MultiClassObjectiveFunction<'_, T, X>
{
fn f(&self, w_bias: &[T]) -> T {
let mut f = T::zero();