StructuredKernelInterpolation

Struct StructuredKernelInterpolation 

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pub struct StructuredKernelInterpolation<K> {
    pub grid_size: Vec<usize>,
    pub kernel: K,
    pub noise_variance: f64,
    pub interpolation: InterpolationMethod,
}
Expand description

Structured Kernel Interpolation (KISS-GP) for fast structured GP inference

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§grid_size: Vec<usize>

Grid size for each dimension

§kernel: K

Kernel function

§noise_variance: f64

Noise variance

§interpolation: InterpolationMethod

Interpolation method

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impl<K> StructuredKernelInterpolation<K>

Builder-style methods for SKI configuration

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pub fn noise_variance(self, noise_variance: f64) -> Self

Set noise variance

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pub fn interpolation(self, interpolation: InterpolationMethod) -> Self

Set interpolation method

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impl<K: SparseKernel> StructuredKernelInterpolation<K>

Structured Kernel Interpolation implementation

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pub fn new(grid_size: Vec<usize>, kernel: K) -> Self

Create new structured kernel interpolation

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pub fn generate_grid_points(&self, x: &Array2<f64>) -> Result<Array2<f64>>

Generate structured grid points over input space

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pub fn compute_interpolation_weights( &self, x: &Array2<f64>, grid_points: &Array2<f64>, ranges: &[(f64, f64)], ) -> Result<Array2<f64>>

Compute interpolation weights for data points to grid

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impl<K: Clone> Clone for StructuredKernelInterpolation<K>

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fn clone(&self) -> StructuredKernelInterpolation<K>

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl<K: Debug> Debug for StructuredKernelInterpolation<K>

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl<K: SparseKernel> Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>> for StructuredKernelInterpolation<K>

Fit implementation for SKI

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type Fitted = FittedSKI<K>

The fitted model type
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fn fit(self, x: &Array2<f64>, y: &Array1<f64>) -> Result<Self::Fitted>

Fit the model to the provided data with validation
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fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>
where Self: Sized,

Fit with custom validation and early stopping

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🔬This is a nightly-only experimental API. (clone_to_uninit)
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