QSVR

class QSVR(*args, quantum_kernel=None, **kwargs)

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)

Tham số

• 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