# Figure out the class distribution percentage and round it to 3 decimal places

print('Percentage of negative class is {} %'.format(
    round(df[target_class_name].value_counts()[0]/len(df) * 100,3)))

print('Percentage of Positive class is {} %'.format(
    round(df[target_class_name].value_counts()[1]/len(df) * 100,3)))

# Watch out for situations where the percentage of one class is really small compared to the other
# In such a scenario we would need to use SMOTE or other balancing techniques