<jupyter_start><jupyter_text>y = -0.45039385x_1 + 0.90057448x_2 + -2.31802434x_3 + -0.97313023<jupyter_code>log.predict_proba(x_train[100:104])
log.predict(x_train[100:104])<jupyter_output><empty_output><jupyter_text>가장 큰 값(높은 확률) 위치<jupyter_code>4.95694448e-04+2.96740147e-01+7.02764158e-01
2.81421455e-06+2.85542460e-02+9.71442940e-01
1.59542795e-02+7.73344928e-01+2.10700793e-01
1.32771319e-04+9.49715503e-02+9.04895678e-01<jupyter_output><empty_output><jupyter_text>evaluation<jupyter_code>from sklearn import metrics
y_pred = log.predict(x_train)
y_pred.shape, y_train.shape
y_pred
y_train
print(metrics.classification_report(y_train, y_pred))
metrics.confusion_matrix(y_train, y_pred)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1388888888888889, 'fraction_numerical': 0.25416666666666665, 'mean_word_length': 9.44927536231884, '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': '456739', 'license': 'Apache-2.0', 'n_tokens_mistral': 457, 'n_tokens_neox': 365, 'n_words': 26, 'path': 'iris_logisticregression.ipynb', 'repo_name': 'webdessin/test_machinelearning', 'size': '720'}