<jupyter_start><jupyter_text>PPFS<jupyter_code>source("PPFS.R")
Paper1Selection = PPFS1(golub_train_predict, golub_train_response, golub_test_predict, golub_test_response)<jupyter_output><empty_output><jupyter_text>Classifier<jupyter_code>source("Classifier.R")
rslt = classifier1(Paper1Selection$train_predict, Paper1Selection$train_response, Paper1Selection$test_predict, Paper1Selection$test_response)<jupyter_output><empty_output><jupyter_text>Show result<jupyter_code>rslt$train
rslt$test<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10325047801147227, 'fraction_numerical': 0.01338432122370937, 'mean_word_length': 29.823529411764707, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '403720', 'license': 'MIT', 'n_tokens_mistral': 202, 'n_tokens_neox': 192, 'n_words': 13, 'path': 'ReproducingMLpipelines/PipelineExample/src/AIM-Layer-Paper1.ipynb', 'repo_name': 'CompareML/AIM-Manuscript', 'size': '523'}