overfitting and spurious final hypothesis
Based on the book page 124125
"On a finite data set, the algorithm inadvertently uses some of the degree of freedom to fit the noise, which can result in overfitting and a spurious final hypothesis."
I have some questions based on this sentence:
1. What is spurious hypothesis? How can we identify the spurious hypothesis?
2. Is there any relationship between overfitting phenomenon and the spurious hypothesis?
3. Does spurious hypothesis come from the impact of deterministic noise in data set?
I got stuck for a while to define spurious hypothesis and how to identify it from the model.
Best Regards,
