- QuantumKernel.evaluate(x_vec, y_vec=None)¶
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.
ndarray) -- 1D or 2D array of datapoints, NxD, where N is the number of datapoints, D is the feature dimension
ndarray]) -- 1D or 2D array of datapoints, MxD, where M is the number of datapoints, D is the feature dimension
- Return type
2D matrix, NxM
A quantum instance or backend has not been provided
unbound user 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.