RandomForest.py 文件源码

def __init__(self, **params):
        """
        Wrapper around sklearn's Random Forest implementation for pyGPGO.
        Random Forests can also be used for surrogate models in Bayesian Optimization.
        An estimate of 'posterior' variance can be obtained by using the `impurity`
        criterion value in each subtree.

        Parameters
        ----------
        params: tuple, optional
            Any parameters to pass to `RandomForestRegressor`. Defaults to sklearn's.

        """
        self.params = params