Struct QuantumMLPRegressor 

pub struct QuantumMLPRegressor { /* private fields */ }

Quantum MLP Regressor (sklearn-compatible)

Implementations

impl QuantumMLPRegressor

pub fn new() -> Self

Create new Quantum MLP Regressor

pub fn set_hidden_layer_sizes(self, sizes: Vec<usize>) -> Self

Set hidden layer sizes

pub fn set_learning_rate(self, lr: f64) -> Self

Set learning rate

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

Set maximum iterations

Trait Implementations

impl Default for QuantumMLPRegressor

fn default() -> Self

Returns the “default value” for a type.

impl SklearnEstimator for QuantumMLPRegressor

fn fit(&mut self, X: &Array2<f64>, y: Option<&Array1<f64>>) -> Result<()>

Fit the model to training data

fn get_params(&self) -> HashMap<String, String>

Get model parameters

fn set_params(&mut self, params: HashMap<String, String>) -> Result<()>

Set model parameters

fn is_fitted(&self) -> bool

Check if model is fitted

fn get_feature_names_out(&self) -> Vec<String>

Get feature names

impl SklearnRegressor for QuantumMLPRegressor

fn predict(&self, X: &Array2<f64>) -> Result<Array1<f64>>

Predict continuous values

fn score(&self, X: &Array2<f64>, y: &Array1<f64>) -> Result<f64>

Score the model (R² by default)