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from sklearn.linear_model import LogisticRegression

from sklearn.metrics import accuracy_score

from sklearn.preprocessing import StandardScaler

import pandas as pd

train = pd.read_csv('/kaggle/input/classification-problem-uni/data_inlf_train.csv', encoding='gbk')

y = train['inlf'].values
train.drop(['inlf'], axis=1, inplace=True)
x = train.values

scaler = StandardScaler()
x = scaler.fit_transform(x)

model = LogisticRegression(max_iter=10000)
model.fit(x, y)

y_pred_class = model.predict(x)
accuracy_score(y, y_pred_class)

test = pd.read_csv('/kaggle/input/classification-problem-uni/data_inlf_test.csv', encoding='gbk')

x = test.values
x = scaler.transform(x)

y_pred_class = model.predict(x)

y_pred_class