def predict_section(classifier, sentence):
"""
Given an input section
:param classifier Classifier to use for prediction
:param sentence Sentence to run prediction on
:return Return predicted section
"""
feature_vector = build_feature_vector(sentence)
return classifier.predict(feature_vector)
def predict_section(classifier, sentence):
"""
Given an input section
:param classifier Classifier to use for prediction
:param sentence Sentence to run prediction on
:return Return predicted section
"""
feature_vector = build_feature_vector(sentence)
return classifier.predict(feature_vector)
def build_classifier():
"""Build and pickle the classifier."""
classes = sections
feature_data = [(tag, build_feature_vector(s)) for (tag, s) in queries]
classifier = MultiClassPerceptron(classes, feature_list, feature_data, train_test_ratio=1)
classifier.train()
with open("classifier.pik", 'wb') as f:
pickle.dump(classifier, f, pickle.HIGHEST_PROTOCOL)
def build_classifier():
"""Build and pickle the classifier."""
classes = sections
feature_data = [(tag, build_feature_vector(s)) for (tag, s) in queries]
classifier = MultiClassPerceptron(classes,
feature_list,
feature_data,
train_test_ratio=1)
classifier.train()
with open("classifier.pik", 'wb') as f:
pickle.dump(classifier, f, pickle.HIGHEST_PROTOCOL)