def test_evaluate_accuracy_rf():
"""Test evaluate_accuracy for rf model"""
classifer = ReviewClassifier('rf')
classifer.load_model(pickle_file='test_rf_model.pickle')
score = classifer.evaluate_accuracy('test-reviews.csv')
assert score > 0
os.remove('output.log')
def test_evaluate_accuracy_nn():
"""Test evaluate_accuracy for nn model"""
classifer = ReviewClassifier('nn')
classifer.load_model(tar_file='test_nn_model.tar')
score = classifer.evaluate_accuracy('test-reviews.csv')
assert score > 0
os.remove('output.log')
def test_load_svm_model():
"""Test load svm model from pickle file"""
classifier = ReviewClassifier('svm')
classifier.load_model(pickle_file='test_svm_model.pickle')
assert classifier.model
assert classifier.vectorizer
assert classifier.encoder
def test_load_nn_model():
"""Test load nn model from tar file"""
classifier = ReviewClassifier('nn')
classifier.load_model(tar_file='test_nn_model.tar')
assert classifier.model
assert classifier.vectorizer
assert classifier.encoder
def test_classify_nn():
"""Test classify using nn"""
classifer = ReviewClassifier('nn')
classifer.load_model(tar_file='test_nn_model.tar')
classifer.classify('classified_comments.txt',
comments_filename='test-reviews.csv')
assert os.path.exists('classified_comments.txt')
os.remove('classified_comments.txt')
def test_classify_rf():
"""Test classify using rf"""
classifer = ReviewClassifier('rf')
classifer.load_model(pickle_file='test_rf_model.pickle')
classifer.classify('classified_comments.txt',
comments_filename='test-reviews.csv')
assert os.path.exists('classified_comments.txt')
os.remove('classified_comments.txt')
def test_classify_nb_from_csv():
"""Test classify using nb model from csv file"""
classifer = ReviewClassifier('nb')
classifer.load_model(pickle_file='test_nb_model.pickle')
classifer.classify('classified_comments.txt',
comments_filename='test-reviews.csv')
assert os.path.exists('classified_comments.txt')
os.remove('classified_comments.txt')
def test_classify_from_text_file():
"""Test classify comments text file"""
classifer = ReviewClassifier('nb')
classifer.load_model(pickle_file='test_nb_model.pickle')
classifer.classify('classified_comments.txt',
comments_text_file='neutral.txt')
assert os.path.exists('classified_comments.txt')
os.remove('classified_comments.txt')
def test_load_nb_model():
"""Test load nb model from pickle file"""
classifier = ReviewClassifier('nb')
classifier.load_model(pickle_file='test_nb_model.pickle')
assert classifier.model
def test_load_model_nn_no_file():
"""Test load nn model without model"""
classifier = ReviewClassifier('nn')
with pytest.raises(Exception):
classifier.load_model()
def test_load_model_nb_no_file():
"""Test load naive bayes model without model"""
classifier = ReviewClassifier('nb')
with pytest.raises(Exception):
classifier.load_model()