Generación de combinaciones de hiperparámetros con ParameterGrid

from sklearn.model_selection import ParameterGrid
from sklearn.svm import SVC

param_grid = [
    # -------------------------------------------------------------------------
    # Primera malla de parámetros
    {
        "kernel": ["rbf"],
        "gamma": [1e-3, 1e-4],
        "C": [1, 10, 100, 1000],
    },
    # -------------------------------------------------------------------------
    # Segunda malla de parámetros
    {
        "kernel": ["linear"],
        "C": [1, 10, 100, 1000],
    },
]

parameterGrid = ParameterGrid(param_grid)

list(parameterGrid)

[{'C': 1, 'gamma': 0.001, 'kernel': 'rbf'},
 {'C': 1, 'gamma': 0.0001, 'kernel': 'rbf'},
 {'C': 10, 'gamma': 0.001, 'kernel': 'rbf'},
 {'C': 10, 'gamma': 0.0001, 'kernel': 'rbf'},
 {'C': 100, 'gamma': 0.001, 'kernel': 'rbf'},
 {'C': 100, 'gamma': 0.0001, 'kernel': 'rbf'},
 {'C': 1000, 'gamma': 0.001, 'kernel': 'rbf'},
 {'C': 1000, 'gamma': 0.0001, 'kernel': 'rbf'},
 {'C': 1, 'kernel': 'linear'},
 {'C': 10, 'kernel': 'linear'},
 {'C': 100, 'kernel': 'linear'},
 {'C': 1000, 'kernel': 'linear'}]