Based on the book "An Introduction to Statistical Learning" I learned that the CV estimate for test MSE has an typical U shape: an increasing degree in the polynomial fits the data better initially but after some point it starts to overfit the training data, which increases the estimated test MSE and gives the U shape.
where minutesDay is the number of minutes since midnight. One can see that there is a jam between 7am and 10am.
Why does the test MSE estimate decreases monotonically?
Is it because the dataset contains an important fraction of almost-duplicated observations (everyday the observations follow the same pattern), so there are high chances of getting a test partition that is very similar to the training partitions?