QSVR¶

class QSVR(*args, quantum_kernel=None, **kwargs)[source]¶

Bases: SVR, SerializableModelMixin

Quantum Support Vector Regressor that extends the scikit-learn sklearn.svm.SVR regressor and introduces an additional quantum_kernel parameter.

This class shows how to use a quantum kernel for regression. The class inherits its methods like fit and predict from scikit-learn, see the example below. Read more in the scikit-learn user guide.

Example

qsvr = QSVR(quantum_kernel=qkernel)
qsvr.fit(sample_train,label_train)
qsvr.predict(sample_test)

Parameters:

quantum_kernel (Optional[BaseKernel]) – Quantum kernel to be used for regression.
*args – Variable length argument list to pass to SVR constructor.
**kwargs – Arbitrary keyword arguments to pass to SVR constructor.

Attributes

quantum_kernel

Returns quantum kernel

Methods