def __init__(self, base_estimator=None, n_estimators=10, max_samples=1.0, max_features=1.0, bootstrap=True,
bootstrap_features=False, oob_score=False, warm_start=False, n_jobs=1, random_state=None, verbose=0):
n_estimators = int(n_estimators)
_BaggingClassifier.__init__(
self, base_estimator, n_estimators, max_samples, max_features, bootstrap, bootstrap_features, oob_score,
warm_start, n_jobs, random_state, verbose)
BaseWrapperClf.__init__(self)
def __init__(self,
classifier=None,
detector=None,
n_estimators=100,
n_jobs=1,
random_state=None,
verbose=0):
BaggingClassifier.__init__(self,
base_estimator=classifier,
n_estimators=n_estimators,
warm_start=False,
n_jobs=n_jobs,
random_state=random_state,
bootstrap=False,
bootstrap_features=False,
verbose=verbose)
self.classifier = classifier
self.detector = detector
def __init__(self,
base_estimator=None,
n_estimators=10,
max_samples=1.0,
max_features=1.0,
bootstrap=True,
bootstrap_features=False,
oob_score=False,
n_jobs=1,
random_state=None,
verbose=0):
BaggingClassifier.__init__(self,
base_estimator=base_estimator,
n_estimators=n_estimators,
max_samples=max_samples,
max_features=max_features,
bootstrap=bootstrap,
bootstrap_features=bootstrap_features,
oob_score=oob_score,
n_jobs=n_jobs,
random_state=random_state,
verbose=verbose)
def __init__(self,
classifier=None,
detector=None,
n_estimators=100,
replacement=True,
sampling_ratio=1.0,
n_jobs=1,
random_state=None,
verbose=0):
BaggingClassifier.__init__(self,
base_estimator=classifier,
warm_start=False,
n_estimators=n_estimators,
n_jobs=n_jobs,
random_state=random_state,
bootstrap=False,
bootstrap_features=False,
verbose=verbose)
self.classifier = classifier
self.detector = detector
self.replacement = replacement
self.sampling_ratio = sampling_ratio
