Struct QuantumTextClassifier 

pub struct QuantumTextClassifier { /* private fields */ }

Quantum text classifier for sentiment analysis and text classification

Implementations

impl QuantumTextClassifier

pub fn new(config: QNLPConfig, num_classes: usize) -> Self

Create a new quantum text classifier

pub fn classify(&self, word_ids: &[usize]) -> QuantRS2Result<Vec<f64>>

Classify a text sequence by running the full quantum forward pass.

The classification circuit is built and simulated exactly; the resulting 2^n Born-rule distribution is reduced to num_classes class scores by marginalising the basis states over the low-order ceil(log2(num_classes)) readout qubits, then renormalised. This is a genuine measurement distribution, not a heuristic.

pub fn build_circuit( &self, word_ids: &[usize], ) -> QuantRS2Result<Vec<Box<dyn GateOp>>>

Generate the full circuit for text classification

pub fn train( &mut self, training_data: &[(Vec<usize>, usize)], learning_rate: f64, epochs: usize, ) -> QuantRS2Result<Vec<f64>>

Train the classifier using a dataset