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)