Struct linfa_pls::PlsRegression [−][src]
pub struct PlsRegression<F: Float>(_);
Implementations
impl<F: Float> PlsRegression<F>
[src]
impl<F: Float> PlsRegression<F>
[src]pub fn params(n_components: usize) -> PlsRegressionParams<F>
[src]
pub fn weights(&self) -> (&Array2<F>, &Array2<F>)
[src]
Singular vectors of the cross-covariance matrices
pub fn loadings(&self) -> (&Array2<F>, &Array2<F>)
[src]
Loadings of records and targets
pub fn rotations(&self) -> (&Array2<F>, &Array2<F>)
[src]
Projection matrices used to transform records and targets
pub fn coefficients(&self) -> &Array2<F>
[src]
The coefficients of the linear model such that Y is approximated as Y = X.coefficients
pub fn inverse_transform(
&self,
dataset: DatasetBase<ArrayBase<impl Data<Elem = F>, Ix2>, ArrayBase<impl Data<Elem = F>, Ix2>>
) -> DatasetBase<Array2<F>, Array2<F>>
[src]
&self,
dataset: DatasetBase<ArrayBase<impl Data<Elem = F>, Ix2>, ArrayBase<impl Data<Elem = F>, Ix2>>
) -> DatasetBase<Array2<F>, Array2<F>>
Transform the given dataset in the projected space back to the original space.
Trait Implementations
impl<F: Float, D: Data<Elem = F>> PredictRef<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for PlsRegression<F>
[src]
impl<F: Float, D: Data<Elem = F>> PredictRef<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for PlsRegression<F>
[src]fn predict_ref<'a>(&'a self, x: &ArrayBase<D, Ix2>) -> Array2<F>
[src]
Given an input matrix X
, with shape (n_samples, n_features)
,
predict
returns the target variable according to [<Pls $name>] method
learned from the training data distribution.
impl<F: Float, D: Data<Elem = F>> Transformer<DatasetBase<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<D, Dim<[usize; 2]>>>, DatasetBase<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>>> for PlsRegression<F>
[src]
impl<F: Float, D: Data<Elem = F>> Transformer<DatasetBase<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<D, Dim<[usize; 2]>>>, DatasetBase<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>>> for PlsRegression<F>
[src]fn transform(
&self,
dataset: DatasetBase<ArrayBase<D, Ix2>, ArrayBase<D, Ix2>>
) -> DatasetBase<Array2<F>, Array2<F>>
[src]
&self,
dataset: DatasetBase<ArrayBase<D, Ix2>, ArrayBase<D, Ix2>>
) -> DatasetBase<Array2<F>, Array2<F>>
Apply dimension reduction to the given dataset
Auto Trait Implementations
impl<F> RefUnwindSafe for PlsRegression<F> where
F: RefUnwindSafe,
impl<F> RefUnwindSafe for PlsRegression<F> where
F: RefUnwindSafe,
impl<F> Send for PlsRegression<F>
impl<F> Send for PlsRegression<F>
impl<F> Sync for PlsRegression<F>
impl<F> Sync for PlsRegression<F>
impl<F> Unpin for PlsRegression<F>
impl<F> Unpin for PlsRegression<F>
impl<F> UnwindSafe for PlsRegression<F> where
F: RefUnwindSafe,
impl<F> UnwindSafe for PlsRegression<F> where
F: RefUnwindSafe,
Blanket Implementations
impl<'a, F, D, T, O> Predict<&'a ArrayBase<D, Dim<[usize; 2]>>, T> for O where
F: Float,
D: Data<Elem = F>,
O: PredictRef<ArrayBase<D, Dim<[usize; 2]>>, T>,
[src]
impl<'a, F, D, T, O> Predict<&'a ArrayBase<D, Dim<[usize; 2]>>, T> for O where
F: Float,
D: Data<Elem = F>,
O: PredictRef<ArrayBase<D, Dim<[usize; 2]>>, T>,
[src]impl<'a, F, R, T, S, O> Predict<&'a DatasetBase<R, T>, S> for O where
F: Float,
R: Records<Elem = F>,
O: PredictRef<R, S>,
[src]
impl<'a, F, R, T, S, O> Predict<&'a DatasetBase<R, T>, S> for O where
F: Float,
R: Records<Elem = F>,
O: PredictRef<R, S>,
[src]pub fn predict(&self, ds: &'a DatasetBase<R, T>) -> S
[src]
impl<F, D, T, O> Predict<ArrayBase<D, Dim<[usize; 2]>>, DatasetBase<ArrayBase<D, Dim<[usize; 2]>>, T>> for O where
F: Float,
D: Data<Elem = F>,
O: PredictRef<ArrayBase<D, Dim<[usize; 2]>>, T>,
[src]
impl<F, D, T, O> Predict<ArrayBase<D, Dim<[usize; 2]>>, DatasetBase<ArrayBase<D, Dim<[usize; 2]>>, T>> for O where
F: Float,
D: Data<Elem = F>,
O: PredictRef<ArrayBase<D, Dim<[usize; 2]>>, T>,
[src]impl<F, R, T, S, O> Predict<DatasetBase<R, T>, DatasetBase<R, S>> for O where
F: Float,
R: Records<Elem = F>,
O: PredictRef<R, S>,
[src]
impl<F, R, T, S, O> Predict<DatasetBase<R, T>, DatasetBase<R, S>> for O where
F: Float,
R: Records<Elem = F>,
O: PredictRef<R, S>,
[src]pub fn predict(&self, ds: DatasetBase<R, T>) -> DatasetBase<R, S>
[src]
impl<V, T> VZip<V> for T where
V: MultiLane<T>,
impl<V, T> VZip<V> for T where
V: MultiLane<T>,