Question 8
Given the code snippet and assume if any necessary requirements:
from sklearn.model_selection import GridSearchCVfrom sklearn.linear_model import LogisticRegressionparam_grid = {'C': [0.1, 1, 10], 'penalty': ['l1', 'l2'], 'solver': ['liblinear']}clf = GridSearchCV(LogisticRegression(), param_grid, cv=5)clf.fit(X_train, y_train)print(clf.best_params_)What does cv=5 signify in this context?
The training data is split into 5 different datasets, each used to train a separate model.
The model is trained and evaluated using 5-fold cross-validation for hyperparameter tuning
Five different models are trained on 5 resampled datasets of training data.
The dataset is divided into 5 parts and trained in a single pass without cross- validation.