def runFromPickle(self, picklefile): f = open(picklefile, "rb") ent_model = pickle.load(f) f.close() print 'Loaded classifier from', picklefile ent = MaximumEntropyClassifier(self.rawfname, **self.maxent_args) ent.setModel(ent_model) return self.evaluate(ent)
def runFromPickle(self, picklefile): ''' Opens the NLTK model stored in <picklefile> and uses that model for evaluation ''' f = open(picklefile, "rb") # Pickle stores an NLTK model ent_model = pickle.load(f) f.close() print 'Loaded classifier from', picklefile ent = MaximumEntropyClassifier(self.rawfname, **self.maxent_args) ent.setModel(ent_model) # Return everything but the classifer string return self.evaluate(ent)[1:]
def runFromPickle(self, picklefile): ''' Opens the NLTK model stored in <picklefile> and uses that model for evaluation ''' f = open(picklefile, "rb") # Pickle stores an NLTK model ent_model = pickle.load(f) f.close() print 'Loaded classifier from', picklefile ent = MaximumEntropyClassifier(self.rawfname, **self.maxent_args) ent.setModel(ent_model) # Return everything but the classifer string return self.evaluate(ent)[1:]