<jupyter_start><jupyter_text>Load Demo DatasetsConvert everything to boolean features.<jupyter_code>from sklearn.datasets import load_breast_cancer
from sklearn.preprocessing import scale
X = scale(load_breast_cancer().data, axis=0) > 0
y = load_breast_cancer().target<jupyter_output><empty_output><jupyter_text>Select Binary Features<jupyter_code>from binsel import binsel_hardvote
%time
idx, neg, rho, results = binsel_hardvote(X, y, oob_score=True)
idx, neg, rho
results<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09145129224652088, 'fraction_numerical': 0.003976143141153081, 'mean_word_length': 9.956521739130435, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 10, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '304407', 'license': 'Apache-2.0', 'n_tokens_mistral': 185, 'n_tokens_neox': 177, 'n_words': 37, 'path': 'examples/binsel_hardvote.ipynb', 'repo_name': 'kmedian/binsel', 'size': '503'}