pub struct BayesianGaussianProcess<F> {
pub x_train: Array2<F>,
pub y_train: Array1<F>,
pub kernel: KernelType,
pub noise_level: F,
pub hyperpriors: HashMap<String, DistributionType<F>>,
pub hyperparameter_samples: Option<Array2<F>>,
}Expand description
Gaussian process regression implementation
Fields§
§x_train: Array2<F>Input data
y_train: Array1<F>Output data
kernel: KernelTypeKernel function
noise_level: FNoise level
hyperpriors: HashMap<String, DistributionType<F>>Hyperpriors for kernel parameters
hyperparameter_samples: Option<Array2<F>>MCMC samples of hyperparameters
Implementations§
Source§impl<F> BayesianGaussianProcess<F>
impl<F> BayesianGaussianProcess<F>
Sourcepub fn new(
x_train: Array2<F>,
y_train: Array1<F>,
kernel: KernelType,
noise_level: F,
) -> StatsResult<Self>
pub fn new( x_train: Array2<F>, y_train: Array1<F>, kernel: KernelType, noise_level: F, ) -> StatsResult<Self>
Create new Gaussian process
Sourcepub fn compute_kernel_matrix(
&self,
x1: &ArrayView2<'_, F>,
x2: &ArrayView2<'_, F>,
) -> StatsResult<Array2<F>>
pub fn compute_kernel_matrix( &self, x1: &ArrayView2<'_, F>, x2: &ArrayView2<'_, F>, ) -> StatsResult<Array2<F>>
Compute kernel matrix
Sourcepub fn predict(
&self,
xtest: &ArrayView2<'_, F>,
) -> StatsResult<(Array1<F>, Array1<F>)>
pub fn predict( &self, xtest: &ArrayView2<'_, F>, ) -> StatsResult<(Array1<F>, Array1<F>)>
Make predictions at new input points
Trait Implementations§
Source§impl<F: Clone> Clone for BayesianGaussianProcess<F>
impl<F: Clone> Clone for BayesianGaussianProcess<F>
Source§fn clone(&self) -> BayesianGaussianProcess<F>
fn clone(&self) -> BayesianGaussianProcess<F>
Returns a duplicate of the value. Read more
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source. Read moreAuto Trait Implementations§
impl<F> Freeze for BayesianGaussianProcess<F>where
F: Freeze,
impl<F> !RefUnwindSafe for BayesianGaussianProcess<F>
impl<F> Send for BayesianGaussianProcess<F>where
F: Send,
impl<F> Sync for BayesianGaussianProcess<F>where
F: Sync,
impl<F> Unpin for BayesianGaussianProcess<F>where
F: Unpin,
impl<F> !UnwindSafe for BayesianGaussianProcess<F>
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
Source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
Source§impl<T> IntoEither for T
impl<T> IntoEither for T
Source§fn into_either(self, into_left: bool) -> Either<Self, Self> ⓘ
fn into_either(self, into_left: bool) -> Either<Self, Self> ⓘ
Converts
self into a Left variant of Either<Self, Self>
if into_left is true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read moreSource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self> ⓘ
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self> ⓘ
Converts
self into a Left variant of Either<Self, Self>
if into_left(&self) returns true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read moreSource§impl<T> Pointable for T
impl<T> Pointable for T
Source§impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
Source§fn to_subset(&self) -> Option<SS>
fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct
self from the equivalent element of its
superset. Read moreSource§fn is_in_subset(&self) -> bool
fn is_in_subset(&self) -> bool
Checks if
self is actually part of its subset T (and can be converted to it).Source§fn to_subset_unchecked(&self) -> SS
fn to_subset_unchecked(&self) -> SS
Use with care! Same as
self.to_subset but without any property checks. Always succeeds.Source§fn from_subset(element: &SS) -> SP
fn from_subset(element: &SS) -> SP
The inclusion map: converts
self to the equivalent element of its superset.