autoemulate.emulators.random_forest

class RandomForest(x, y, standardize_x=False, standardize_y=False, n_estimators=100, criterion='squared_error', max_depth=None, min_samples_split=2, min_samples_leaf=1, max_features=1.0, bootstrap=True, oob_score=False, max_samples=None, random_seed=None, device='cpu', **kwargs)

Bases: SklearnBackend

Random forest Emulator.

Implements Random Forests regression from scikit-learn.

static is_multioutput()

Random forests support multi-output.

static get_tune_params()

Return a dictionary of hyperparameters to tune.