def fit(self, data_matrix, data_matrix_neg, random_state=None):
if random_state is not None:
random.seed(random_state)
# use eden to fitoooOoO
self.estimator = eden_fit_estimator(self.classifier, positive_data_matrix=data_matrix,
negative_data_matrix=data_matrix_neg,
cv=self.cv,
n_jobs=self.n_jobs,
n_iter_search=10,
random_state=random_state)
self.cal_estimator = self.estimator
self.status = 'trained'
return self
def fit_estimator(self, data_matrix, n_jobs=-1, cv=2, random_state=42):
'''
create self.estimator...
by inversing the data_matrix set to get a negative set
and then using edens fit_estimator
'''
# make negative set
data_matrix_neg = data_matrix.multiply(-1)
return eden_fit_estimator(self.classifier,
positive_data_matrix=data_matrix,
negative_data_matrix=data_matrix_neg,
cv=cv,
n_jobs=n_jobs,
n_iter_search=10,
random_state=random_state)
def fit_estimator(self, data_matrix, n_jobs=-1, cv=2, random_state=42):
'''
create self.estimator...
by inversing the data_matrix set to get a negative set
and then using edens fit_estimator
'''
# create negative set:
data_matrix_neg = data_matrix.multiply(-1)
# i hope loss is log.. not 100% sure..
# probably calibration will fix this#
return eden_fit_estimator(SGDClassifier(loss='log'), positive_data_matrix=data_matrix,
negative_data_matrix=data_matrix_neg,
cv=cv,
n_jobs=n_jobs,
n_iter_search=10,
random_state=random_state)
def make_estimator(pos,neg):
pos = vectorizer.transform( pos )
neg = vectorizer.transform( neg )
esti = eden_fit_estimator(SGDClassifier(), positive_data_matrix=pos,
negative_data_matrix=neg)
return esti
def make_estimator(pos,neg):
pos = vectorizer.transform( pos )
neg = vectorizer.transform( neg )
esti = eden_fit_estimator(SGDClassifier(), positive_data_matrix=pos,
negative_data_matrix=neg)
return esti
def get_estimator(it_pos, it_neg):
pos = vect.transform(it_pos)
neg = vect.transform(it_neg)
return eden_fit_estimator(SGDClassifier(), pos, neg)
def get_estimator(it_pos, it_neg):
pos= vect.transform(it_pos)
neg = vect.transform(it_neg)
return eden_fit_estimator(SGDClassifier(),pos,neg)
