Struct linfa_linear::FittedTweedieRegressor

pub struct FittedTweedieRegressor<A> {
    pub coef: Array1<A>,
    pub intercept: A,
    // some fields omitted
}

Fitted Tweedie regressor model for scoring

Fields

coef: Array1<A>

Estimated coefficients for the linear predictor

intercept: A

Intercept or bias added to the linear model

Trait Implementations

impl<'de, A> Deserialize<'de> for FittedTweedieRegressor<A> where
    A: Deserialize<'de>, 

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<A: Float, D: Data<Elem = A>> PredictRef<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<A>, Dim<[usize; 1]>>> for FittedTweedieRegressor<A>

fn predict_ref<'a>(&'a self, x: &ArrayBase<D, Ix2>) -> Array1<A>

Predict the target

impl<A> Serialize for FittedTweedieRegressor<A> where
    A: Serialize, 

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.