Struct linfa_linear::TweedieRegressor
source · [−]pub struct TweedieRegressor<A> {
pub coef: Array1<A>,
pub intercept: A,
/* private fields */
}Expand description
Fitted Tweedie regressor model for scoring
Fields
coef: Array1<A>Estimated coefficients for the linear predictor
intercept: AIntercept or bias added to the linear model
Implementations
sourceimpl<F: Float> TweedieRegressor<F>
impl<F: Float> TweedieRegressor<F>
Trait Implementations
sourceimpl<A: Clone> Clone for TweedieRegressor<A>
impl<A: Clone> Clone for TweedieRegressor<A>
sourcefn clone(&self) -> TweedieRegressor<A>
fn clone(&self) -> TweedieRegressor<A>
Returns a copy of the value. Read more
1.0.0 · sourcefn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from source. Read more
sourceimpl<A: Debug> Debug for TweedieRegressor<A>
impl<A: Debug> Debug for TweedieRegressor<A>
sourceimpl<'de, A> Deserialize<'de> for TweedieRegressor<A> where
A: Deserialize<'de>,
impl<'de, A> Deserialize<'de> for TweedieRegressor<A> where
A: Deserialize<'de>,
sourcefn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
sourceimpl<A: PartialEq> PartialEq<TweedieRegressor<A>> for TweedieRegressor<A>
impl<A: PartialEq> PartialEq<TweedieRegressor<A>> for TweedieRegressor<A>
sourcefn eq(&self, other: &TweedieRegressor<A>) -> bool
fn eq(&self, other: &TweedieRegressor<A>) -> bool
This method tests for self and other values to be equal, and is used
by ==. Read more
sourcefn ne(&self, other: &TweedieRegressor<A>) -> bool
fn ne(&self, other: &TweedieRegressor<A>) -> bool
This method tests for !=.
sourceimpl<A: Float, D: Data<Elem = A>> PredictInplace<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<A>, Dim<[usize; 1]>>> for TweedieRegressor<A>
impl<A: Float, D: Data<Elem = A>> PredictInplace<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<A>, Dim<[usize; 1]>>> for TweedieRegressor<A>
sourcefn predict_inplace(&self, x: &ArrayBase<D, Ix2>, y: &mut Array1<A>)
fn predict_inplace(&self, x: &ArrayBase<D, Ix2>, y: &mut Array1<A>)
Predict the target
sourcefn default_target(&self, x: &ArrayBase<D, Ix2>) -> Array1<A>
fn default_target(&self, x: &ArrayBase<D, Ix2>) -> Array1<A>
Create targets that predict_inplace works with.
sourceimpl<A> Serialize for TweedieRegressor<A> where
A: Serialize,
impl<A> Serialize for TweedieRegressor<A> where
A: Serialize,
impl<A> StructuralPartialEq for TweedieRegressor<A>
Auto Trait Implementations
impl<A> RefUnwindSafe for TweedieRegressor<A> where
A: RefUnwindSafe,
impl<A> Send for TweedieRegressor<A> where
A: Send,
impl<A> Sync for TweedieRegressor<A> where
A: Sync,
impl<A> Unpin for TweedieRegressor<A> where
A: Unpin,
impl<A> UnwindSafe for TweedieRegressor<A> where
A: UnwindSafe + RefUnwindSafe,
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more