3 ms·
This is only going to get worse. I see literally no counter force putting any kind of barrier against the incentive to e.g. overfit in order to get exaggerated
by tw1010 8y ago
This is only going to get worse. I see literally no counter force putting any kind of barrier against the incentive to e.g. overfit in order to get exaggerated results. The lucrative reward is too large not to fall for the use of shady tactics (which are sometimes not even consciously obvious; not being critical enough of your own work is a form of model loosening which acts in favour of more impressive results).
- nonbel 8y agoThis is everywhere in academia. Peer review is like the goggles in the face of a seemingly neverending wave of BS: https://www.youtube.com/watch?v=juFZh92MUOY https://www.youtube.com/watch?v=juFZh92MUOY Honestly who cares about these papers in the case of ML though? Its not like running other experiments where you cant check it yourself without spending $100k. Just share the code and explain it in a blog or readme. Its usually some pdf with equations no one is solving, proofs based on assumptions that dont apply to my situations, and some cherry picked overfitting of the cv.