pub struct QuantumMLEngine { /* private fields */ }Expand description
Quantum machine learning engine with comprehensive algorithm support
Implementations§
Source§impl QuantumMLEngine
impl QuantumMLEngine
Sourcepub fn new(config: QuantumConfig) -> Self
pub fn new(config: QuantumConfig) -> Self
Create a new quantum ML engine
Sourcepub async fn train_qnn(
&self,
training_data: Vec<(Vec<f64>, Vec<f64>)>,
epochs: usize,
) -> Result<QuantumTrainingStats>
pub async fn train_qnn( &self, training_data: Vec<(Vec<f64>, Vec<f64>)>, epochs: usize, ) -> Result<QuantumTrainingStats>
Train the quantum neural network
Sourcepub async fn register_model(&self, model: QuantumModel) -> Result<()>
pub async fn register_model(&self, model: QuantumModel) -> Result<()>
Register a trained model
Sourcepub async fn get_training_stats(&self) -> QuantumTrainingStats
pub async fn get_training_stats(&self) -> QuantumTrainingStats
Get training statistics
Sourcepub fn get_algorithms(&self) -> &[QuantumMLAlgorithm]
pub fn get_algorithms(&self) -> &[QuantumMLAlgorithm]
Get available algorithms
Sourcepub async fn create_qsvm(
&self,
training_data: Vec<(Vec<f64>, f64)>,
) -> Result<QuantumModel>
pub async fn create_qsvm( &self, training_data: Vec<(Vec<f64>, f64)>, ) -> Result<QuantumModel>
Create a quantum support vector machine
Sourcepub async fn create_qpca(&self, data: Vec<Vec<f64>>) -> Result<QuantumModel>
pub async fn create_qpca(&self, data: Vec<Vec<f64>>) -> Result<QuantumModel>
Create a quantum principal component analysis model
Auto Trait Implementations§
impl Freeze for QuantumMLEngine
impl !RefUnwindSafe for QuantumMLEngine
impl Send for QuantumMLEngine
impl Sync for QuantumMLEngine
impl Unpin for QuantumMLEngine
impl !UnwindSafe for QuantumMLEngine
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impl<T> BorrowMut<T> for Twhere
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Mutably borrows from an owned value. Read more
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The inclusion map: converts
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