def unigram(train_sentences, test_sentences):
# processing of the sentences to tagged samples, since there's no importance to sentences structure
train = sentences_to_samples(train_sentences)
test = sentences_to_samples(test_sentences)
unigram_HMM = Unigram(train)
unigram_HMM.train()
# initialisation of lists of samples containing known and unknown words
test_known_words, test_unknown_words = divide_test_to_known_and_unknown_samples(
train_sentences, test_sentences)
# evaluation of the accuracy for each case
print("Accuracy rate for unknown words: ",
unigram_HMM.get_accuracy_rate(np.array(test_unknown_words)))
print("Accuracy rate for known words: ",
unigram_HMM.get_accuracy_rate(np.array(test_known_words)))
print("Total accuracy rate: ",
unigram_HMM.get_accuracy_rate(np.array(test)))
