<jupyter_start><jupyter_text>Classification Report<jupyter_code>print(classification_report(test_set_y_orig,y_predicted_labels));<jupyter_output>precision    recall  f1-score   support

           0       0.95      1.00      0.98        20
           1       0.87      1.00      0.93        20
           2       0.89      0.85      0.87        20
           3       0.95      1.00      0.98        20
           4       1.00      0.85      0.92        20
           5       1.00      0.95      0.97        20

    accuracy                           0.94       120
   macro avg       0.94      0.94      0.94       120
weighted avg       0.94      0.94      0.94       120
{'fraction_non_alphanumeric': 0.05952380952380952, 'fraction_numerical': 0.15327380952380953, 'mean_word_length': 0.8140161725067385, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 8, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '524837', 'license': 'MIT', 'n_tokens_mistral': 257, 'n_tokens_neox': 216, 'n_words': 50, 'path': 'Hand sign recognition.ipynb', 'repo_name': 'MSTC-DA-IICT/Data-Science-Machine-Learning', 'size': '672'}