QuantumKernel.evaluate¶
- QuantumKernel.evaluate(x_vec, y_vec=None)[source]¶
Construct kernel matrix for given data and feature map
If y_vec is None, self inner product is calculated. If using statevector_simulator, only build circuits for \(\Psi(x)|0\rangle\), then perform inner product classically.
- Parameters:
- Return type:
- Returns:
2D matrix, NxM
- Raises:
A quantum instance or backend has not been provided
unbound training parameters in the feature map circuit - x_vec and/or y_vec are not one or two dimensional arrays - x_vec and y_vec have have incompatible dimensions - x_vec and/or y_vec have incompatible dimension with feature map and and feature map can not be modified to match.