Struct RandomFourierFeatures 

pub struct RandomFourierFeatures;

Random Fourier Features approximation method RandomFourierFeatures

Trait Implementations

impl ApproximationMethod for RandomFourierFeatures

const NAME: &'static str = "RandomFourierFeatures"

Name of the approximation method

const SUPPORTS_INCREMENTAL: bool = true

Whether this method supports incremental updates

const HAS_ERROR_BOUNDS: bool = true

Whether this method provides theoretical error bounds

const COMPLEXITY: ComplexityClass = ComplexityClass::Linear

Computational complexity class

impl ApproximationQualityBounds<RandomFourierFeatures> for ()

const ERROR_BOUND_CONSTANT: f64 = 2f64

Theoretical error bound for this method

const SAMPLE_COMPLEXITY_EXPONENT: f64 = 0.25f64

Sample complexity scaling

const DIMENSION_DEPENDENCY: f64 = 0.10000000000000001f64

Dimension dependency

fn error_bound(n_samples: usize, n_features: usize, n_components: usize) -> f64

Compute theoretical error bound

impl Clone for RandomFourierFeatures

fn clone(&self) -> RandomFourierFeatures

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for RandomFourierFeatures

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

Formats the value using the given formatter.

impl KernelMethodCompatibility<ArcCosineKernel, RandomFourierFeatures> for ()

Arc-cosine kernels have limited compatibility

const IS_COMPATIBLE: bool = true

Whether this kernel-method combination is supported

const PERFORMANCE_TIER: PerformanceTier = PerformanceTier::Acceptable

Performance characteristics of this combination

const MEMORY_COMPLEXITY: ComplexityClass = ComplexityClass::Linear

Memory complexity

impl KernelMethodCompatibility<LaplacianKernel, RandomFourierFeatures> for ()

const IS_COMPATIBLE: bool = true

Whether this kernel-method combination is supported

const PERFORMANCE_TIER: PerformanceTier = PerformanceTier::Optimal

Performance characteristics of this combination

const MEMORY_COMPLEXITY: ComplexityClass = ComplexityClass::Linear

Memory complexity

impl KernelMethodCompatibility<PolynomialKernel, RandomFourierFeatures> for ()

const IS_COMPATIBLE: bool = true

Whether this kernel-method combination is supported

const PERFORMANCE_TIER: PerformanceTier = PerformanceTier::Good

Performance characteristics of this combination

const MEMORY_COMPLEXITY: ComplexityClass = ComplexityClass::Linear

Memory complexity

impl KernelMethodCompatibility<RBFKernel, RandomFourierFeatures> for ()

Implement compatibility rules

const IS_COMPATIBLE: bool = true

Whether this kernel-method combination is supported

const PERFORMANCE_TIER: PerformanceTier = PerformanceTier::Optimal

Performance characteristics of this combination

const MEMORY_COMPLEXITY: ComplexityClass = ComplexityClass::Linear

Memory complexity

impl Copy for RandomFourierFeatures

impl FittableKernel<RandomFourierFeatures> for LaplacianKernel

impl FittableKernel<RandomFourierFeatures> for RBFKernel

impl FittableMethod<LaplacianKernel> for RandomFourierFeatures

impl FittableMethod<RBFKernel> for RandomFourierFeatures