Índice

A

ad_hoc_data() (en el módulo qiskit_machine_learning.datasets) add_note() (método de QiskitMachineLearningError) ansatz (atributo de QNNCircuit) (atributo de VQC) (atributo de VQR)

assign_training_parameters() (método de TrainableFidelityQuantumKernel) (método de TrainableFidelityStatevectorKernel) (método de TrainableKernel)

B

backward() (método de EstimatorQNN) (método de NeuralNetwork) (método de SamplerQNN)

BaseKernel (clase en qiskit_machine_learning.kernels) BinaryObjectiveFunction (clase en qiskit_machine_learning.algorithms)

C

callback (atributo de NeuralNetworkClassifier) (atributo de NeuralNetworkRegressor) (atributo de TrainableModel) (atributo de VQC) (atributo de VQR) circuit (atributo de EstimatorQNN) (atributo de SamplerQNN) (atributo de VQC)

class_weight_ (atributo de QSVR) clear_cache() (método de FidelityStatevectorKernel) (método de TrainableFidelityStatevectorKernel) coef_ (atributo de QSVC) (atributo de QSVR) combine() (método de QuantumKernelTrainerResult) CrossEntropyLoss (clase en qiskit_machine_learning.utils.loss_functions)

D

decision_function() (método de PegasosQSVC) (método de QSVC)

E

EffectiveDimension (clase en qiskit_machine_learning.neural_networks) enforce_psd (atributo de BaseKernel) (atributo de FidelityQuantumKernel) (atributo de FidelityStatevectorKernel) (atributo de TrainableFidelityQuantumKernel) (atributo de TrainableFidelityStatevectorKernel) (atributo de TrainableKernel) estimator (atributo de EstimatorQNN) EstimatorQNN (clase en qiskit_machine_learning.neural_networks) evaluate() (método de BaseKernel) (método de CrossEntropyLoss) (método de FidelityQuantumKernel) (método de FidelityStatevectorKernel) (método de KernelLoss) (método de L1Loss) (método de L2Loss) (método de Loss) (método de SVCLoss) (método de TrainableFidelityQuantumKernel) (método de TrainableFidelityStatevectorKernel) (método de TrainableKernel)

evaluate_duplicates (atributo de FidelityQuantumKernel) (atributo de TrainableFidelityQuantumKernel)

F

feature_dimension (atributo de RawFeatureVector) feature_map (atributo de BaseKernel) (atributo de FidelityQuantumKernel) (atributo de FidelityStatevectorKernel) (atributo de QNNCircuit) (atributo de TrainableFidelityQuantumKernel) (atributo de TrainableFidelityStatevectorKernel) (atributo de TrainableKernel) (atributo de VQC) (atributo de VQR) fidelity (atributo de FidelityQuantumKernel) (atributo de TrainableFidelityQuantumKernel) FidelityQuantumKernel (clase en qiskit_machine_learning.kernels) FidelityStatevectorKernel (clase en qiskit_machine_learning.kernels) fit() (método de NeuralNetworkClassifier) (método de NeuralNetworkRegressor) (método de PegasosQSVC) (método de QSVC) (método de QSVR) (método de QuantumKernelTrainer) (método de TrainableModel) (método de VQC) (método de VQR)

fit_result (atributo de NeuralNetworkClassifier) (atributo de NeuralNetworkRegressor) (atributo de TrainableModel) (atributo de VQC) (atributo de VQR) FITTED (atributo de PegasosQSVC) forward() (método de EstimatorQNN) (método de NeuralNetwork) (método de SamplerQNN) (método de TorchConnector)

G

get_effective_dimension() (método de EffectiveDimension) (método de LocalEffectiveDimension) get_fisher_information() (método de EffectiveDimension) (método de LocalEffectiveDimension) get_metadata_routing() (método de QSVC) (método de QSVR) get_normalized_fisher() (método de EffectiveDimension) (método de LocalEffectiveDimension) get_params() (método de QSVC) (método de QSVR)

gradient (atributo de EstimatorQNN) (atributo de SamplerQNN) gradient() (método de BinaryObjectiveFunction) (método de CrossEntropyLoss) (método de L1Loss) (método de L2Loss) (método de Loss) (método de MultiClassObjectiveFunction) (método de ObjectiveFunction) (método de OneHotObjectiveFunction)

I

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

input_parameters (atributo de QNNCircuit) input_params (atributo de EstimatorQNN) (atributo de SamplerQNN) input_samples (atributo de EffectiveDimension) (atributo de LocalEffectiveDimension) interpret (atributo de SamplerQNN)

K

KernelLoss (clase en qiskit_machine_learning.utils.loss_functions)

L

L1Loss (clase en qiskit_machine_learning.utils.loss_functions) L2Loss (clase en qiskit_machine_learning.utils.loss_functions) load() (método de clase de NeuralNetworkClassifier) (método de clase de NeuralNetworkRegressor) (método de clase de PegasosQSVC) (método de clase de QSVC) (método de clase de QSVR) (método de clase de SerializableModelMixin) (método de clase de TrainableModel) (método de clase de VQC) (método de clase de VQR)

LocalEffectiveDimension (clase en qiskit_machine_learning.neural_networks) loss (atributo de NeuralNetworkClassifier) (atributo de NeuralNetworkRegressor) (atributo de QuantumKernelTrainer) (atributo de TrainableModel) (atributo de VQC) (atributo de VQR) Loss (clase en 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 (clase en qiskit_machine_learning.algorithms)

N

n_support_ (atributo de QSVC) (atributo de QSVR) neural_network (atributo de NeuralNetworkClassifier) (atributo de NeuralNetworkRegressor) (atributo de TorchConnector) (atributo de TrainableModel) (atributo de VQC) (atributo de VQR) NeuralNetwork (clase en qiskit_machine_learning.neural_networks) NeuralNetworkClassifier (clase en qiskit_machine_learning.algorithms) NeuralNetworkRegressor (clase en qiskit_machine_learning.algorithms) num_classes (atributo de NeuralNetworkClassifier) (atributo de VQC) num_features (atributo de BaseKernel) (atributo de FidelityQuantumKernel) (atributo de FidelityStatevectorKernel) (atributo de TrainableFidelityQuantumKernel) (atributo de TrainableFidelityStatevectorKernel) (atributo de TrainableKernel)

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

O

objective() (método de BinaryObjectiveFunction) (método de MultiClassObjectiveFunction) (método de ObjectiveFunction) (método de OneHotObjectiveFunction) ObjectiveFunction (clase en qiskit_machine_learning.algorithms) observables (atributo de EstimatorQNN) OneHotObjectiveFunction (clase en qiskit_machine_learning.algorithms) optimal_circuit (atributo de QuantumKernelTrainerResult) optimal_parameters (atributo de QuantumKernelTrainerResult) optimal_point (atributo de QuantumKernelTrainerResult) optimal_value (atributo de QuantumKernelTrainerResult)

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

P

parameter_values (atributo de TrainableFidelityQuantumKernel) (atributo de TrainableFidelityStatevectorKernel) (atributo de TrainableKernel) PegasosQSVC (clase en qiskit_machine_learning.algorithms) precomputed (atributo de PegasosQSVC) predict() (método de NeuralNetworkClassifier) (método de NeuralNetworkRegressor) (método de PegasosQSVC) (método de QSVC) (método de QSVR) (método de TrainableModel) (método de VQC) (método de VQR)

predict_log_proba() (método de QSVC) predict_proba() (método de QSVC) probA_ (atributo de QSVC) probB_ (atributo de 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 (clase en qiskit_machine_learning.circuit.library) QSVC (clase en qiskit_machine_learning.algorithms) QSVR (clase en qiskit_machine_learning.algorithms) quantum_kernel (atributo de PegasosQSVC) (atributo de QSVC) (atributo de QSVR) (atributo de QuantumKernelTrainer) (atributo de QuantumKernelTrainerResult) QuantumKernelTrainer (clase en qiskit_machine_learning.kernels.algorithms) QuantumKernelTrainerResult (clase en qiskit_machine_learning.kernels.algorithms)

R

RawFeatureVector (clase en qiskit_machine_learning.circuit.library)

run_monte_carlo() (método de EffectiveDimension) (método de LocalEffectiveDimension)

S

sampler (atributo de SamplerQNN) SamplerQNN (clase en qiskit_machine_learning.neural_networks) save() (método de NeuralNetworkClassifier) (método de NeuralNetworkRegressor) (método de PegasosQSVC) (método de QSVC) (método de QSVR) (método de SerializableModelMixin) (método de TrainableModel) (método de VQC) (método de VQR) score() (método de NeuralNetworkClassifier) (método de NeuralNetworkRegressor) (método de PegasosQSVC) (método de QSVC) (método de QSVR) (método de TrainableModel) (método de VQC) (método de VQR)

SerializableModelMixin (clase en qiskit_machine_learning.algorithms) set_fit_request() (método de QSVC) (método de QSVR) set_interpret() (método de SamplerQNN) set_params() (método de QSVC) (método de QSVR) set_score_request() (método de QSVC) (método de QSVR) sparse (atributo de EstimatorQNN) (atributo de NeuralNetwork) (atributo de SamplerQNN) (atributo de TorchConnector) SVCLoss (clase en qiskit_machine_learning.utils.loss_functions)

T

TorchConnector (clase en qiskit_machine_learning.connectors) TrainableFidelityQuantumKernel (clase en qiskit_machine_learning.kernels) TrainableFidelityStatevectorKernel (clase en qiskit_machine_learning.kernels) TrainableKernel (clase en qiskit_machine_learning.kernels)

TrainableModel (clase en qiskit_machine_learning.algorithms) training_parameters (atributo de TrainableFidelityQuantumKernel) (atributo de TrainableFidelityStatevectorKernel) (atributo de TrainableKernel)

U

UNFITTED (atributo de PegasosQSVC)

unused_param (atributo de QSVC) (atributo de QSVR)

V

VQC (clase en qiskit_machine_learning.algorithms)

VQR (clase en qiskit_machine_learning.algorithms)

W

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

weight_samples (atributo de EffectiveDimension) (atributo de LocalEffectiveDimension) weights (atributo de NeuralNetworkClassifier) (atributo de NeuralNetworkRegressor) (atributo de TrainableModel) (atributo de VQC) (atributo de VQR) with_traceback() (método de QiskitMachineLearningError)