{'fraction_non_alphanumeric': 0.010126582278481013, 'fraction_numerical': 0.005063291139240506, 'mean_word_length': 5.491803278688525, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Evaluating Text Clustering Methods for Text Classification

In this project report, I will evaluate the several text clustering approaches and how they can be used for the purpose of text classification. The particular task is topic classification of 20 Newsgroup dataset and sentiment classification restaurant reviews dataset. Future direction for improving the results will also be discussed.