<jupyter_start><jupyter_text>for inum, each_t in enumerate(target):    labels = np.unique(y_test[:,inum])  sometimes there is less classes    plot_classification_results(y_test[:,inum], y_preds[:,inum], labels, labels, each_t)<jupyter_code>#print_regression_model_stats(y_test, y_preds)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12658227848101267, 'fraction_numerical': 0.0, 'mean_word_length': 10.74074074074074, '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': '537508', 'license': 'Apache-2.0', 'n_tokens_mistral': 119, 'n_tokens_neox': 117, 'n_words': 18, 'path': 'examples/Deep_Auto_ViML_Titanic.ipynb', 'repo_name': 'rajeevkumarsah/deep_autoviml', 'size': '316'}