Struct Pca 

pub struct Pca {
    pub n_components: usize,
}

Parameters for PCA (unfitted state).

Principal Component Analysis reduces dimensionality by projecting data onto the directions of maximum variance. Eigendecomposition is performed via power iteration with deflation, requiring no external LAPACK dependency.

Fields

n_components: usize

Number of principal components to keep.

Implementations

impl Pca

pub fn new(n_components: usize) -> Self

Create a new Pca with the given number of components.

Trait Implementations

impl Clone for Pca

fn clone(&self) -> Pca

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Pca

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for Pca

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<F: Float> FitUnsupervised<F> for Pca

type Fitted = FittedPca<F>

fn fit(&self, x: &Array2<F>) -> Result<Self::Fitted>

impl Serialize for Pca

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.