<jupyter_start><jupyter_text>**Red circles represent list of customers that didn't get approval, and green circles represent those who got approval.**<jupyter_code>#Finding the frauds
mappings = som.win_map(X)
mappings
frauds = np.concatenate((mappings[(1,2)], mappings[(4,4)]), axis = 0)
frauds = sc.inverse_transform(frauds)
frauds
frauds = pd.DataFrame(frauds)
frauds<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1225, 'fraction_numerical': 0.0125, 'mean_word_length': 8.113636363636363, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '145718', 'license': 'Apache-2.0', 'n_tokens_mistral': 157, 'n_tokens_neox': 136, 'n_words': 34, 'path': 'Labs/Lab2/Heenal/SOM_CreditCardFraud.ipynb', 'repo_name': 'heenalsapovadia/ml_practices_2018', 'size': '400'}