Table 6 Hyperparameters control various aspects of the QSVM model for text classification.
From: Quantum computing and machine learning for Arabic language sentiment classification in social media
Hyperparameter | Description | Value |
|---|---|---|
feature_map | Feature map encoding the input data | None |
Optimizer | Classical optimizer used for training the QSVM model | COBYLA |
SVM | Support vector machine (SVM) implementation used in the QSVM model | CircuitQNN |
Multiclass_extension | Multiclass extension method for binary classification | OneAgainstRest |
Quantum_instance | Backend on which the quantum algorithm is executed | None |
Shots | Number of repetitions of the circuit execution | 1024 |
Gamma | Coefficient for the RBF (Radial Basis Function) kernel | None |
C | Regularization parameter for the SVM classifier | 1.0 |
Random_seed | Seed for the random number generator | None |
Tolerance | Convergence tolerance for the optimizer | 0.0001 |
Max_iterations | Maximum number of iterations for the optimizer | 100 |
