Index

A

ad_hoc_data() (dans le module qiskit_machine_learning.datasets) add_note() (méthode QiskitMachineLearningError) ansatz (attribut QNNCircuit) (attribut VQC) (attribut VQR)

assign_training_parameters() (méthode TrainableFidelityQuantumKernel) (méthode TrainableFidelityStatevectorKernel) (méthode TrainableKernel)

B

backward() (méthode EstimatorQNN) (méthode NeuralNetwork) (méthode SamplerQNN)

BaseKernel (classe dans qiskit_machine_learning.kernels) BinaryObjectiveFunction (classe dans qiskit_machine_learning.algorithms)

C

callback (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut TrainableModel) (attribut VQC) (attribut VQR) circuit (attribut EstimatorQNN) (attribut SamplerQNN) (attribut VQC)

class_weight_ (attribut QSVR) clear_cache() (méthode FidelityStatevectorKernel) (méthode TrainableFidelityStatevectorKernel) coef_ (attribut QSVC) (attribut QSVR) combine() (méthode QuantumKernelTrainerResult) CrossEntropyLoss (classe dans qiskit_machine_learning.utils.loss_functions)

D

decision_function() (méthode PegasosQSVC) (méthode QSVC)

E

EffectiveDimension (classe dans qiskit_machine_learning.neural_networks) enforce_psd (attribut BaseKernel) (attribut FidelityQuantumKernel) (attribut FidelityStatevectorKernel) (attribut TrainableFidelityQuantumKernel) (attribut TrainableFidelityStatevectorKernel) (attribut TrainableKernel) estimator (attribut EstimatorQNN) EstimatorQNN (classe dans qiskit_machine_learning.neural_networks) evaluate() (méthode BaseKernel) (méthode CrossEntropyLoss) (méthode FidelityQuantumKernel) (méthode FidelityStatevectorKernel) (méthode KernelLoss) (méthode L1Loss) (méthode L2Loss) (méthode Loss) (méthode SVCLoss) (méthode TrainableFidelityQuantumKernel) (méthode TrainableFidelityStatevectorKernel) (méthode TrainableKernel)

evaluate_duplicates (attribut FidelityQuantumKernel) (attribut TrainableFidelityQuantumKernel)

F

feature_dimension (attribut RawFeatureVector) feature_map (attribut BaseKernel) (attribut FidelityQuantumKernel) (attribut FidelityStatevectorKernel) (attribut QNNCircuit) (attribut TrainableFidelityQuantumKernel) (attribut TrainableFidelityStatevectorKernel) (attribut TrainableKernel) (attribut VQC) (attribut VQR) fidelity (attribut FidelityQuantumKernel) (attribut TrainableFidelityQuantumKernel) FidelityQuantumKernel (classe dans qiskit_machine_learning.kernels) FidelityStatevectorKernel (classe dans qiskit_machine_learning.kernels) fit() (méthode NeuralNetworkClassifier) (méthode NeuralNetworkRegressor) (méthode PegasosQSVC) (méthode QSVC) (méthode QSVR) (méthode QuantumKernelTrainer) (méthode TrainableModel) (méthode VQC) (méthode VQR)

fit_result (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut TrainableModel) (attribut VQC) (attribut VQR) FITTED (attribut PegasosQSVC) forward() (méthode EstimatorQNN) (méthode NeuralNetwork) (méthode SamplerQNN) (méthode TorchConnector)

G

get_effective_dimension() (méthode EffectiveDimension) (méthode LocalEffectiveDimension) get_fisher_information() (méthode EffectiveDimension) (méthode LocalEffectiveDimension) get_metadata_routing() (méthode QSVC) (méthode QSVR) get_normalized_fisher() (méthode EffectiveDimension) (méthode LocalEffectiveDimension) get_params() (méthode QSVC) (méthode QSVR)

gradient (attribut EstimatorQNN) (attribut SamplerQNN) gradient() (méthode BinaryObjectiveFunction) (méthode CrossEntropyLoss) (méthode L1Loss) (méthode L2Loss) (méthode Loss) (méthode MultiClassObjectiveFunction) (méthode ObjectiveFunction) (méthode OneHotObjectiveFunction)

I

initial_point (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut QuantumKernelTrainer) (attribut TrainableModel) (attribut VQC) (attribut VQR) input_gradients (attribut EstimatorQNN) (attribut NeuralNetwork) (attribut SamplerQNN)

input_parameters (attribut QNNCircuit) input_params (attribut EstimatorQNN) (attribut SamplerQNN) input_samples (attribut EffectiveDimension) (attribut LocalEffectiveDimension) interpret (attribut SamplerQNN)

K

KernelLoss (classe dans qiskit_machine_learning.utils.loss_functions)

L

L1Loss (classe dans qiskit_machine_learning.utils.loss_functions) L2Loss (classe dans qiskit_machine_learning.utils.loss_functions) load() (méthode de la classe NeuralNetworkClassifier) (méthode de la classe NeuralNetworkRegressor) (méthode de la classe PegasosQSVC) (méthode de la classe QSVC) (méthode de la classe QSVR) (méthode de la classe SerializableModelMixin) (méthode de la classe TrainableModel) (méthode de la classe VQC) (méthode de la classe VQR)

LocalEffectiveDimension (classe dans qiskit_machine_learning.neural_networks) loss (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut QuantumKernelTrainer) (attribut TrainableModel) (attribut VQC) (attribut VQR) Loss (classe dans qiskit_machine_learning.utils.loss_functions)

M

module qiskit_machine_learning qiskit_machine_learning.algorithms qiskit_machine_learning.circuit.library qiskit_machine_learning.connectors qiskit_machine_learning.datasets qiskit_machine_learning.kernels qiskit_machine_learning.kernels.algorithms qiskit_machine_learning.neural_networks qiskit_machine_learning.utils qiskit_machine_learning.utils.loss_functions

MultiClassObjectiveFunction (classe dans qiskit_machine_learning.algorithms)

N

n_support_ (attribut QSVC) (attribut QSVR) neural_network (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut TorchConnector) (attribut TrainableModel) (attribut VQC) (attribut VQR) NeuralNetwork (classe dans qiskit_machine_learning.neural_networks) NeuralNetworkClassifier (classe dans qiskit_machine_learning.algorithms) NeuralNetworkRegressor (classe dans qiskit_machine_learning.algorithms) num_classes (attribut NeuralNetworkClassifier) (attribut VQC) num_features (attribut BaseKernel) (attribut FidelityQuantumKernel) (attribut FidelityStatevectorKernel) (attribut TrainableFidelityQuantumKernel) (attribut TrainableFidelityStatevectorKernel) (attribut TrainableKernel)

num_input_parameters (attribut QNNCircuit) num_inputs (attribut EstimatorQNN) (attribut NeuralNetwork) (attribut SamplerQNN) num_qubits (attribut QNNCircuit) (attribut RawFeatureVector) (attribut VQC) (attribut VQR) num_steps (attribut PegasosQSVC) num_training_parameters (attribut TrainableFidelityQuantumKernel) (attribut TrainableFidelityStatevectorKernel) (attribut TrainableKernel) num_weight_parameters (attribut QNNCircuit) num_weights (attribut EstimatorQNN) (attribut NeuralNetwork) (attribut SamplerQNN)

O

objective() (méthode BinaryObjectiveFunction) (méthode MultiClassObjectiveFunction) (méthode ObjectiveFunction) (méthode OneHotObjectiveFunction) ObjectiveFunction (classe dans qiskit_machine_learning.algorithms) observables (attribut EstimatorQNN) OneHotObjectiveFunction (classe dans qiskit_machine_learning.algorithms) optimal_circuit (attribut QuantumKernelTrainerResult) optimal_parameters (attribut QuantumKernelTrainerResult) optimal_point (attribut QuantumKernelTrainerResult) optimal_value (attribut QuantumKernelTrainerResult)

optimizer (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut QuantumKernelTrainer) (attribut TrainableModel) (attribut VQC) (attribut VQR) optimizer_evals (attribut QuantumKernelTrainerResult) optimizer_result (attribut QuantumKernelTrainerResult) optimizer_time (attribut QuantumKernelTrainerResult) output_shape (attribut EstimatorQNN) (attribut NeuralNetwork) (attribut SamplerQNN)

P

parameter_values (attribut TrainableFidelityQuantumKernel) (attribut TrainableFidelityStatevectorKernel) (attribut TrainableKernel) PegasosQSVC (classe dans qiskit_machine_learning.algorithms) precomputed (attribut PegasosQSVC) predict() (méthode NeuralNetworkClassifier) (méthode NeuralNetworkRegressor) (méthode PegasosQSVC) (méthode QSVC) (méthode QSVR) (méthode TrainableModel) (méthode VQC) (méthode VQR)

predict_log_proba() (méthode QSVC) predict_proba() (méthode QSVC) probA_ (attribut QSVC) probB_ (attribut QSVC)

Q

qiskit_machine_learning module qiskit_machine_learning.algorithms module qiskit_machine_learning.circuit.library module qiskit_machine_learning.connectors module qiskit_machine_learning.datasets module qiskit_machine_learning.kernels module qiskit_machine_learning.kernels.algorithms module qiskit_machine_learning.neural_networks module

qiskit_machine_learning.utils module qiskit_machine_learning.utils.loss_functions module QiskitMachineLearningError QNNCircuit (classe dans qiskit_machine_learning.circuit.library) QSVC (classe dans qiskit_machine_learning.algorithms) QSVR (classe dans qiskit_machine_learning.algorithms) quantum_kernel (attribut PegasosQSVC) (attribut QSVC) (attribut QSVR) (attribut QuantumKernelTrainer) (attribut QuantumKernelTrainerResult) QuantumKernelTrainer (classe dans qiskit_machine_learning.kernels.algorithms) QuantumKernelTrainerResult (classe dans qiskit_machine_learning.kernels.algorithms)

R

RawFeatureVector (classe dans qiskit_machine_learning.circuit.library)

run_monte_carlo() (méthode EffectiveDimension) (méthode LocalEffectiveDimension)

S

sampler (attribut SamplerQNN) SamplerQNN (classe dans qiskit_machine_learning.neural_networks) save() (méthode NeuralNetworkClassifier) (méthode NeuralNetworkRegressor) (méthode PegasosQSVC) (méthode QSVC) (méthode QSVR) (méthode SerializableModelMixin) (méthode TrainableModel) (méthode VQC) (méthode VQR) score() (méthode NeuralNetworkClassifier) (méthode NeuralNetworkRegressor) (méthode PegasosQSVC) (méthode QSVC) (méthode QSVR) (méthode TrainableModel) (méthode VQC) (méthode VQR)

SerializableModelMixin (classe dans qiskit_machine_learning.algorithms) set_fit_request() (méthode QSVC) (méthode QSVR) set_interpret() (méthode SamplerQNN) set_params() (méthode QSVC) (méthode QSVR) set_score_request() (méthode QSVC) (méthode QSVR) sparse (attribut EstimatorQNN) (attribut NeuralNetwork) (attribut SamplerQNN) (attribut TorchConnector) SVCLoss (classe dans qiskit_machine_learning.utils.loss_functions)

T

TorchConnector (classe dans qiskit_machine_learning.connectors) TrainableFidelityQuantumKernel (classe dans qiskit_machine_learning.kernels) TrainableFidelityStatevectorKernel (classe dans qiskit_machine_learning.kernels) TrainableKernel (classe dans qiskit_machine_learning.kernels)

TrainableModel (classe dans qiskit_machine_learning.algorithms) training_parameters (attribut TrainableFidelityQuantumKernel) (attribut TrainableFidelityStatevectorKernel) (attribut TrainableKernel)

U

UNFITTED (attribut PegasosQSVC)

unused_param (attribut QSVC) (attribut QSVR)

V

VQC (classe dans qiskit_machine_learning.algorithms)

VQR (classe dans qiskit_machine_learning.algorithms)

W

warm_start (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut TrainableModel) (attribut VQC) (attribut VQR) weight (attribut TorchConnector) weight_parameters (attribut QNNCircuit) weight_params (attribut EstimatorQNN) (attribut SamplerQNN)

weight_samples (attribut EffectiveDimension) (attribut LocalEffectiveDimension) weights (attribut NeuralNetworkClassifier) (attribut NeuralNetworkRegressor) (attribut TrainableModel) (attribut VQC) (attribut VQR) with_traceback() (méthode QiskitMachineLearningError)