def __init__(self,
criterion='mselin',
splitter='best',
max_depth=None,
min_samples_split=2,
min_samples_leaf=1,
min_weight_fraction_leaf=0.0,
max_features=None,
random_state=None,
max_leaf_nodes=None,
min_impurity_decrease=0.0,
min_impurity_split=None):
DecisionTreeRegressor.__init__(
self,
criterion=criterion,
splitter=splitter,
max_depth=max_depth,
min_samples_split=min_samples_split,
min_samples_leaf=min_samples_leaf,
min_weight_fraction_leaf=min_weight_fraction_leaf,
max_features=max_features,
random_state=random_state,
max_leaf_nodes=max_leaf_nodes,
min_impurity_decrease=min_impurity_decrease,
min_impurity_split=min_impurity_split)
def __init__(self, criterion="mse", splitter="best", max_depth=None, min_samples_split=2, min_samples_leaf=1,
min_weight_fraction_leaf=0., max_features=None, random_state=None, max_leaf_nodes=None,
min_impurity_decrease=0., min_impurity_split=None, presort=False):
_DecisionTreeRegressor.__init__(
self, criterion, splitter, max_depth, min_samples_split, min_samples_leaf, min_weight_fraction_leaf,
max_features, random_state, max_leaf_nodes, min_impurity_decrease, min_impurity_split, presort)
BaseWrapperReg.__init__(self)
def __init__(self, marginal_kdes=False, joint_kdes=False, **kwargs):
DecisionTreeRegressor.__init__(self, **kwargs)
self.marginal_kdes_ = marginal_kdes
self.joint_kdes_ = joint_kdes
return
def __init__(self):
DecisionTreeRegressor.__init__(self, random_state=0)
def __init__(self):
DecisionTreeRegressor.__init__(self)
def __init__(self):
DecisionTreeRegressor.__init__(self,
max_depth=20,
min_samples_split=40,
min_impurity_decrease=0.01,
min_impurity_split=0.5)
