Struct DictionaryLearning 

pub struct DictionaryLearning<State = Untrained> { /* private fields */ }

Dictionary Learning estimator

Implementations

impl DictionaryLearning<Untrained>

pub fn new(config: DictionaryLearningConfig) -> Self

Create a new dictionary learning instance

pub fn builder() -> DictionaryLearningBuilder

Builder pattern constructor

impl DictionaryLearning<Trained>

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

Get the dictionary components

pub fn n_iter(&self) -> usize

Get the number of iterations performed

Trait Implementations

impl<State: Clone> Clone for DictionaryLearning<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 DictionaryLearning<State>

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

Formats the value using the given formatter.

impl<'de, State> Deserialize<'de> for DictionaryLearning<State>

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Estimator for DictionaryLearning<Untrained>

type Config = DictionaryLearningConfig

Configuration type for the estimator

type Error = SklearsError

Error type for the estimator

type Float = f64

The numeric type used by this estimator

fn config(&self) -> &Self::Config

Get estimator configuration

fn validate_config(&self) -> Result<(), SklearsError>

Validate estimator configuration with detailed error context

fn check_compatibility( &self, n_samples: usize, n_features: usize, ) -> Result<(), SklearsError>

Check if estimator is compatible with given data dimensions

fn metadata(&self) -> EstimatorMetadata

Get estimator metadata

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

type Fitted = DictionaryLearning<Trained>

The fitted model type

fn fit(self, x: &Array2<Float>, _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<State> Serialize for DictionaryLearning<State>

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for DictionaryLearning<Trained>

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

Transform the input data