def __init__(self, n=3, glm=False):
Reader.__init__(self, n=n)
Tagger.__init__(self, glm=glm)
self.tags = set()
self.tokens = set()
self.emission_params = {}
self.transition_params = {}
def __init__(self):
Tagger.__init__(self)
self.upos = []
self.model = Pipeline([
('vectorizer', DictVectorizer()),
('classifier', LogisticRegressionCV(Cs=10, fit_intercept=True, cv=None, dual=False, penalty='l2', scoring=None, \
solver='lbfgs', tol=0.0001, max_iter=100, class_weight=None, n_jobs=1, verbose=0, refit=True, intercept_scaling=1.0, \
multi_class='ovr', random_state=None))
])
