Struct Autoencoder 

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

Simple Autoencoder model

Implementations

impl Autoencoder<Untrained>

pub fn new() -> Self

Create a new autoencoder

pub fn encoding_dim(self, dim: usize) -> Self

Set encoding dimension

pub fn activation(self, activation: Activation) -> Self

Set activation function

pub fn learning_rate(self, lr: Float) -> Self

Set learning rate

pub fn n_epochs(self, epochs: usize) -> Self

Set number of epochs

pub fn batch_size(self, size: usize) -> Self

Set batch size

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

Set random state

pub fn encoder_layers(self, layers: Vec<usize>) -> Self

Set encoder layers for deep autoencoder

pub fn noise_factor(self, factor: Float) -> Self

Set noise factor for denoising autoencoder

pub fn l2_reg(self, reg: Float) -> Self

Set L2 regularization parameter

pub fn sparsity(self, rho: Float, beta: Float) -> Self

Set sparsity parameters (rho, beta)

pub fn optimizer(self, opt: OptimizerType) -> Self

Set optimizer type

impl Autoencoder<Trained>

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

Reconstruct data (encode then decode)

Trait Implementations

impl<State: Clone> Clone for Autoencoder<State>

fn clone(&self) -> Autoencoder<State>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<State: Debug> Debug for Autoencoder<State>

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

Formats the value using the given formatter.

impl Default for Autoencoder<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for Autoencoder<Untrained>

type Config = AutoencoderConfig

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 Autoencoder<Untrained>

type Fitted = Autoencoder<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 Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for Autoencoder<Trained>

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

Transform data to encoded representation