def test_classify_test_dataset():
"""
This will attempt to classify the test dataset
"""
start_time = time.time()
classifier.train()
number_of_reviews = classifier.negative_review_count + classifier.positive_review_count
results = classifier.predict_reviews()
print(results)
print(
str(results["correct_predictions"] / number_of_reviews * 100) +
"% is the accuracy ")
final_time = time.time() - start_time
print("It took: " f'{final_time:.2f}' " seconds to run\n")
def test_classify_train_dataset_with_testing_data_with_stopwords():
"""
This will attempt to classify the training dataset, using the testing dataset to train - with stop-words
"""
start_time = time.time()
classifier.train(use_testing_data=True)
number_of_reviews = classifier.negative_review_count + classifier.positive_review_count
results = classifier.predict_reviews(use_stop_words=True,
classify_training_data=True)
print(results)
print(
str(results["correct_predictions"] / number_of_reviews * 100) +
"% is the accuracy ")
final_time = time.time() - start_time
print("It took: " f'{final_time:.2f}' " seconds to run\n")