def __init__(self,
max_depth=defaults_parameters["max_depth"],
n_estimators=defaults_parameters["n_estimators"],
learning_rate=defaults_parameters["learning_rate"]):
ClassifierTask.__init__(self)
self.max_depth = max_depth
self.n_estimators = n_estimators
self.learning_rate = learning_rate
def __init__(self,
kernel=defaults_parameters["kernel"],
C=defaults_parameters["C"],
degree=defaults_parameters["degree"],
gamma=defaults_parameters["gamma"]):
ClassifierTask.__init__(self)
self.__kernel__ = kernel
self.__C__ = C
self.__degree__ = degree
self.__gamma__ = gamma
def __init__(self,
penalty=defaults_parameters["penalty"],
dual=defaults_parameters["dual"],
C=defaults_parameters["C"],
fit_intercept=defaults_parameters["fit_intercept"]):
ClassifierTask.__init__(self)
self.__penalty__ = penalty
self.__dual__ = dual
self.__C__ = C
self.__fit_intercept__ = fit_intercept
def __init__(self,
criterion=defaults_parameters["criterion"],
max_depth=defaults_parameters["max_depth"],
min_samples_split=defaults_parameters["min_samples_split"],
min_samples_leaf=defaults_parameters["min_samples_leaf"]):
ClassifierTask.__init__(self)
self.__criterion__ = criterion
self.__max_depth__ = max_depth
self.__min_samples_split__ = min_samples_split
self.__min_samples_leaf__ = min_samples_leaf
def __init__(self,
n_neighbors=defaults_parameters["n_neighbors"],
algorithm=defaults_parameters["algorithm"],
weights=defaults_parameters["weights"],
leaf_size=defaults_parameters["leaf_size"],
metric=defaults_parameters["metric"]):
ClassifierTask.__init__(self)
self.__n_neighbors__ = n_neighbors
self.__algorithm__ = algorithm
self.__weights__ = weights
self.__leaf_size__ = leaf_size
self.__metric__ = metric
def __init__(self,
n_estimators=defaults_parameters["n_estimators"],
criterion=defaults_parameters["criterion"],
max_depth=defaults_parameters["max_depth"],
min_samples_split=defaults_parameters["min_samples_split"],
min_samples_leaf=defaults_parameters["min_samples_leaf"]):
ClassifierTask.__init__(self)
self.n_estimators = n_estimators
self.criterion = criterion
self.min_samples_split = min_samples_split
self.min_samples_leaf = min_samples_leaf
self.max_depth = max_depth
def __init__(self):
ClassifierTask.__init__(self)
self.__base_estimator__ = None
def __init__(self):
ClassifierTask.__init__(self)
def __init__(self,
base_estimator=defaults_parameters["base_estimator"],
n_estimators=defaults_parameters["n_estimators"]):
ClassifierTask.__init__(self)
self.__base_estimator__ = base_estimator
self.__n_estimators__ = n_estimators