[−][src]Struct smartcore::ensemble::random_forest_regressor::RandomForestRegressorParameters
Parameters of the Random Forest Regressor Some parameters here are passed directly into base estimator.
Fields
max_depth: Option<u16>
Tree max depth. See Decision Tree Regressor
min_samples_leaf: usize
The minimum number of samples required to be at a leaf node. See Decision Tree Regressor
min_samples_split: usize
The minimum number of samples required to split an internal node. See Decision Tree Regressor
n_trees: usize
The number of trees in the forest.
m: Option<usize>
Number of random sample of predictors to use as split candidates.
Implementations
impl RandomForestRegressorParameters
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pub fn with_max_depth(self, max_depth: u16) -> Self
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Tree max depth. See Decision Tree Classifier
pub fn with_min_samples_leaf(self, min_samples_leaf: usize) -> Self
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The minimum number of samples required to be at a leaf node. See Decision Tree Classifier
pub fn with_min_samples_split(self, min_samples_split: usize) -> Self
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The minimum number of samples required to split an internal node. See Decision Tree Classifier
pub fn with_n_trees(self, n_trees: usize) -> Self
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The number of trees in the forest.
pub fn with_m(self, m: usize) -> Self
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Number of random sample of predictors to use as split candidates.
Trait Implementations
impl Clone for RandomForestRegressorParameters
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pub fn clone(&self) -> RandomForestRegressorParameters
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pub fn clone_from(&mut self, source: &Self)
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impl Debug for RandomForestRegressorParameters
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impl Default for RandomForestRegressorParameters
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impl<'de> Deserialize<'de> for RandomForestRegressorParameters
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pub fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
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__D: Deserializer<'de>,
impl Serialize for RandomForestRegressorParameters
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pub fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
__S: Serializer,
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__S: Serializer,
impl<T: RealNumber, M: Matrix<T>> SupervisedEstimator<M, <M as BaseMatrix<T>>::RowVector, RandomForestRegressorParameters> for RandomForestRegressor<T>
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Auto Trait Implementations
impl RefUnwindSafe for RandomForestRegressorParameters
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impl Send for RandomForestRegressorParameters
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impl Sync for RandomForestRegressorParameters
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impl Unpin for RandomForestRegressorParameters
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impl UnwindSafe for RandomForestRegressorParameters
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Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> DeserializeOwned for T where
T: for<'de> Deserialize<'de>,
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T: for<'de> Deserialize<'de>,
impl<T> From<T> for T
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
The type returned in the event of a conversion error.
pub fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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impl<V, T> VZip<V> for T where
V: MultiLane<T>,
V: MultiLane<T>,