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from sklearn.linear_model import LogisticRegression

from sklearn.metrics import classification_report, confusion_matrix, accuracy_score

from sklearn.pipeline import Pipeline

from sklearn.preprocessing import MinMaxScaler

from sklearn.pipeline import Pipeline
from sklearn.preprocessing import MinMaxScaler
scaler = MinMaxScaler()
lr = LogisticRegression(solver='liblinear')
lgr_classifier = Pipeline([('scale', scaler), ('lr', lr)])
lgr_classifier.fit(X_train, y_train)
lgr_prediction = lgr_classifier.predict(X_test)

print(classification_report(y_test, lgr_prediction))
print(confusion_matrix(y_test, lgr_prediction))