Struct NMF 

pub struct NMF<State = Untrained> {
    pub n_components: usize,
    pub init: NMFInit,
    pub solver: NMFSolver,
    pub regularization: NMFRegularization,
    pub alpha_w: f64,
    pub alpha_h: f64,
    pub l1_ratio: f64,
    pub max_iter: usize,
    pub tol: f64,
    pub random_state: Option<u64>,
    /* private fields */
}

Non-negative Matrix Factorization transformer

Fields

n_components: usize

Number of components/topics

init: NMFInit

Initialization method

solver: NMFSolver

Solver algorithm

regularization: NMFRegularization

Regularization type

alpha_w: f64

L1 regularization strength

alpha_h: f64

L2 regularization strength

l1_ratio: f64

L1 ratio for elastic net regularization

max_iter: usize

Maximum number of iterations

tol: f64

Tolerance for convergence

random_state: Option<u64>

Random state for reproducibility

Implementations

impl NMF<Untrained>

pub fn new(n_components: usize) -> Self

Create a new NMF transformer

pub fn init(self, init: NMFInit) -> Self

Set the initialization method

pub fn solver(self, solver: NMFSolver) -> Self

Set the solver algorithm

pub fn regularization( self, regularization: NMFRegularization, alpha: f64, ) -> Self

Set regularization parameters

pub fn l1_ratio(self, l1_ratio: f64) -> Self

Set L1 ratio for elastic net

pub fn max_iter(self, max_iter: usize) -> Self

Set maximum iterations

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

Set tolerance

pub fn random_state(self, random_state: u64) -> Self

Set random state

impl NMF<TrainedNMF>

pub fn components(&self) -> Array2<f64>

Get the components matrix (W)

pub fn n_iter(&self) -> usize

Get the number of iterations performed

pub fn reconstruction_err(&self) -> f64

Get the reconstruction error

pub fn inverse_transform(&self, h: &Array2<f64>) -> Result<Array2<f64>>

Inverse transform (reconstruct data from components)

Trait Implementations

impl<State: Clone> Clone for NMF<State>

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<State: Debug> Debug for NMF<State>

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

Formats the value using the given formatter.

impl Default for NMF<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ()> for NMF<Untrained>

type Fitted = NMF<TrainedNMF>

The fitted model type

fn fit(self, x: &Array2<f64>, _y: &()) -> Result<Self::Fitted>

Fit the model to the provided data with validation

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

impl Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for NMF<TrainedNMF>

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

Transform the input data