Overfitting with Polynomials : deterministic noise
I have some difficulty to understand the idea of deterministic noise. I think there are some disturbing contradiction with what we've seen with the biasvariance tradeoff, particularly with 50th order noiseless target exemple.
Chapter 4 state that:
 A 2nd order polynomial could be better than a 10th order polynomial to fit a 50th order polynomial target and it's due to the deterministic noise.
> So I conclude that there is more deterministic noise with 10th order than with the 2nd order.
 Deterministic noise=bias
But we've seen with the biasvariance tradeoff, that a more complex model than an other have a lower bias.
Obvioulsy, I'm wrong somewhere, but where ?
