<jupyter_start><jupyter_text>survived,  pclass,  sibsp, parch, fare<jupyter_code>X = df[['pclass','sibsp', 'parch', 'fare']]
Y = df[['survived']]
X.shape, Y.shape
from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test = train_test_split(X,Y)
X_train.shape, X_test.shape, Y_train.shape, Y_test.shape
from sklearn.linear_model import LogisticRegression
logR = LogisticRegression()
logR, type(logR)
logR.fit(X_train,Y_train)
logR.classes_
logR.coef_
logR.score(X_train, Y_train)
from sklearn import metrics<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1276595744680851, 'fraction_numerical': 0.0, 'mean_word_length': 8.416666666666666, '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': '283258', 'license': 'Apache-2.0', 'n_tokens_mistral': 234, 'n_tokens_neox': 233, 'n_words': 42, 'path': 'classfication.ipynb', 'repo_name': 'yoojunwoong/machinelearning2', 'size': '564'}