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()