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import pandas as pd
from sklearn.metrics import mean_squared_error
from ... # import model you picked from its module

df = pd.read_csv('/datasets/train_data_us.csv')

# initialize variables:
features = 
target = 

final_model = # initialize constructor for model that had the best RMSE value 
final_model.fit(...) # train model on training set

print("\nRMSE of the final model on the training set:", mean_squared_error(target, final_model.predict(features), squared=False))
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