Evaluation doubt

[Fabio Gobbato]

In the evaluation function is it better to have a few weights but well tuned or more weights not well tuned?
What does your experience say?

[ZirconiumX]

Fewer, but better. Fewer weights helps with orthogonality, and the tuning may well make up for the missing terms. Plus, the terms will harmonise themselves with your search, increasing search speed.

[BeyondCritics]

Read chapter 5 of this book
http://www.deeplearningbook.org/
anf you can dicuss the question yourself. Or read any introduction into "Machine Learning".

[Ferdy]

Read chapter 5 of this book
http://www.deeplearningbook.org/
anf you can dicuss the question yourself. Or read any introduction into "Machine Learning".

Good info, thanks.

[Fabio Gobbato]

Of course less weights are easier to tune, but even if they are well tuned they can't express all the knowledge of a more complex evaluation.
So the answer is not so easy.