lr_baseline.py

# Modeling the data as is
# Train model
lr = LogisticRegression(solver='liblinear').fit(X_train, y_train)
 
# Predict on training set
lr_pred = lr.predict(X_test)

# Checking accuracy
accuracy_score(y_test, lr_pred)
    0.9992

# Checking unique values
predictions = pd.DataFrame(lr_pred)
predictions[0].value_counts()
    0    71108
    1       94