Struct PCAParameters

pub struct PCAParameters {
    pub n_components: usize,
    pub use_correlation_matrix: bool,
}

PCA parameters

Fields

n_components: usize

Number of components to keep.

use_correlation_matrix: bool

By default, covariance matrix is used to compute principal components. Enable this flag if you want to use correlation matrix instead.

Implementations

impl PCAParameters

pub fn with_n_components(self, n_components: usize) -> Self

Number of components to keep.

pub fn with_use_correlation_matrix(self, use_correlation_matrix: bool) -> Self

By default, covariance matrix is used to compute principal components. Enable this flag if you want to use correlation matrix instead.

Trait Implementations

impl Clone for PCAParameters

fn clone(&self) -> PCAParameters

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for PCAParameters

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

Formats the value using the given formatter.

impl Default for PCAParameters

fn default() -> Self

Returns the “default value” for a type.

impl<T: Number + RealNumber, X: Array2<T> + SVDDecomposable<T> + EVDDecomposable<T>> UnsupervisedEstimator<X, PCAParameters> for PCA<T, X>

fn fit(x: &X, parameters: PCAParameters) -> Result<Self, Failed>

Fit a model to a training dataset, estimate model’s parameters.