def _get_train_stream(self, data): """ returns training instances stream from data file name or data source""" feature_alphabet = self._feature_alphabet if isinstance(data, str): stream = Source(data, feature_alphabet=feature_alphabet, alphabet_lock=False, alphabet_pop=False, bias=self._bias) elif isinstance(data, Source): stream = data elif callable(data): stream = Source(data, feature_alphabet=feature_alphabet, alphabet_lock=False, alphabet_pop=False, bias=self._bias) else: raise Exception( "Error: data is either string for file name or ClassificationSource!" ) # set alphabet from data self.set_alphabet(stream.get_alphabet()) return stream
def _get_test_stream( self, data ): """ returns test instances stream from data file name or data source""" if isinstance(data,str): stream = Source( data, alphabet_lock=True,\ alphabet_pop=False, bias=self._bias ) elif isinstance(data,Source): stream = data else: raise Exception("Error: data is either string for file name or ClassificationSource!") # use model alphabet stream.set_alphabet( self.get_alphabet() ) return stream
def _get_test_stream(self, data): """ returns test instances stream from data file name or data source""" if isinstance(data, str): stream = Source( data, alphabet_lock=True,\ alphabet_pop=False, bias=self._bias ) elif isinstance(data, Source): stream = data else: raise Exception( "Error: data is either string for file name or ClassificationSource!" ) # use model alphabet stream.set_alphabet(self.get_alphabet()) return stream
def _get_train_stream( self, data ): """ returns training instances stream from data file name or data source""" feature_alphabet = self._feature_alphabet if isinstance(data,str): stream = Source(data, feature_alphabet=feature_alphabet, alphabet_lock=False, alphabet_pop=False, bias=self._bias) elif isinstance(data,Source): stream = data elif callable(data): stream = Source(data, feature_alphabet=feature_alphabet, alphabet_lock=False, alphabet_pop=False, bias=self._bias) else: raise Exception("Error: data is either string for file name or ClassificationSource!") # set alphabet from data self.set_alphabet( stream.get_alphabet() ) return stream