Quantum Kernel #2
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attp
requested review from
manoelmarques,
pbark,
stefan-woerner and
woodsp-ibm
as code owners
woodsp-ibm
reviewed
Mar 4, 2021
|
@stefan-woerner previously you mentioned that the |
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@attp let's leave as is with feature map and quantum instance. |
Now that I'm adding documentation and tests, it makes more sense to initialise |
…n check for no features in evaluaute Added new test case for no feature map provided
…accordingly. Changed tests to match.
woodsp-ibm
reviewed
Mar 18, 2021
woodsp-ibm
reviewed
Mar 18, 2021
woodsp-ibm
reviewed
Mar 18, 2021
woodsp-ibm
reviewed
Mar 18, 2021
Fixed comments in qsvc and test_qsvc
woodsp-ibm
approved these changes
Mar 21, 2021
gentinettagian
pushed a commit
to gentinettagian/qiskit-machine-learning
that referenced
this pull request
Dec 14, 2021
* Added quantum_kernel, qsvc and qsvr classes. * Add quantum kernel tests and tutorial * add QuantumKernel to html docs * Added default feature map. * Add QSVR * Changed default feature map to PauliFeatureMap, with no features, then check for no features in evaluaute Added new test case for no feature map provided * Changed QSVC to take a quantum kernl and added tests * Made ZZFeatureMap with 2 qubits default and modified evaluate method accordingly. Changed tests to match. * Edited QSVC and QSVR classes to take QuantumKernel. * Changed enforce_psd default to true. Added more details to init docstring. * Added tests for sending arguments to SVC constructor. * Updated qsvr and made test_qsvr Fixed comments in qsvc and test_qsvc * Renamed quantum kernel tutorial and added example using qsvc * Modifed test_qkernel since default for enforce_psd is now True, not False. Co-authored-by: Manoel Marques <Manoel.Marques@ibm.com>
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Class (
quantum_kernel.py) that calculates a quantum kernel for use in scikit-learn machine learning algorithms for classification (qsvc.py) and regression (qsvr.py) algorithms.To do:
qsvcandqsvrqsvcandqsvr