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:]
