def __init__(self,
base_model=LinearSVC(),
num_models=50,
bagging_percent=0.5,
bagging_replacement=True,
feature_subset_percent=1.0,
weighting=None,
stacking_model=None,
randomize_params={},
verbose=False):
BaseEnsemble.__init__(
self,
base_model,
num_models,
bagging_percent,
bagging_replacement,
feature_subset_percent,
stacking_model,
randomize_params,
False, # for now additive only works for regression
verbose)
self.weighting = weighting
self.classes = None
self.class_list = None
def __init__(self,
base_model = LinearSVC(),
num_models = 50,
bagging_percent=0.5,
bagging_replacement=True,
feature_subset_percent = 1.0,
weighting = None,
stacking_model = None,
randomize_params = {},
verbose=False):
BaseEnsemble.__init__(
self,
base_model,
num_models,
bagging_percent,
bagging_replacement,
feature_subset_percent,
stacking_model,
randomize_params,
False, # for now additive only works for regression
verbose)
self.weighting = weighting
self.classes = None
self.class_list = None
def __init__(self,
base_model=LinearRegression(),
num_models=50,
bagging_percent=0.5,
bagging_replacement=True,
feature_subset_percent=1.0,
stacking_model=None,
randomize_params={},
additive=False,
verbose=False):
BaseEnsemble.__init__(self, base_model, num_models, bagging_percent,
bagging_replacement, feature_subset_percent,
stacking_model, randomize_params, additive,
verbose)
def __init__(self,
base_model=LinearRegression(),
num_models = 50,
bagging_percent=0.5,
bagging_replacement=True,
feature_subset_percent = 1.0,
stacking_model=None,
randomize_params = {},
additive = False,
verbose=False):
BaseEnsemble.__init__(self,
base_model,
num_models,
bagging_percent,
bagging_replacement,
feature_subset_percent,
stacking_model,
randomize_params,
additive,
verbose)
