def __init__(self, debug=False, log=None, data_dir="data", clf_type=None):
if clf_type is None:
self.__print__('ERR', 'unable to create SentiAnalys obj: no classificator type')
sys.exit(1)
TextParser.__init__(self, debug, log, data_dir)
self.senti_class = ['нейтральная', 'позитивная', 'негативная']
if clf_type == 0:
clf_fname = 'log_clf.model'
elif clf_type == 1:
clf_fname = 'xgboost_clf.model'
else:
self.__print__('ERR', 'unable to create SentiAnalys obj: incorrect classificator type {}'.format(clf_type))
sys.exit(1)
self.clf_type = clf_type
try:
clf_f = open(clf_fname, 'r')
self.clf = pickle.load(clf_f)
# TODO: check clf type
clf_f.close()
except Exception as e:
self.__print__('ERR', "unable to init SentiAnalys obj: {}".format(e))
def __init__(self, batch_size=50, debug=False, log=None, data_dir="data"): TextParser.__init__(self, debug, log, data_dir) self.db_cn = DBConnector() self.__select_news_agent_info__() self.batch_size = batch_size
def __init__(self, debug=False, log=None, data_dir="data"):
TextParser.__init__(self, debug, log, data_dir)
def __init__(self, batch_size=50, debug=False, log=None, data_dir="data"):
TextParser.__init__(self, debug, log, data_dir)
self.db_cn = DBConnector()
self.__select_news_agent_info__()
self.batch_size = batch_size
def __init__(self, debug=False, log=None, data_dir="data"): TextParser.__init__(self, debug, log, data_dir)
