[SiempreViernes]

Calling it ”overfitting” is actually you overfitting your model of how theory works on this one concept from machine learning.

The actual events of the 750 GeV peak are much closer to neural networks hallucinating, and the diversity of models created doesen’t strike me as evidence of overfitting...

Anyway, you clearly didn’t trust my summary, and I no longer trust you have an honest interest in learning more, so I’ll stop here.

[nonbel]

If you can come up with 300 different explanations for a random blip, your theory is obviously very flexible. You are probably overfitting.

If your solution to the problem of not being able to generalize your model to new/other data is to add more parameters. You are probably overfitting.

These are the hallmarks of overfitting.

Sorry that you cannot learn from others and only expect them to learn from you.

[SiempreViernes]

Look at this: theorists come up with something like 300 different models, and you declare they all used the same theory to do it? Of course they didn't! Why would you assume they all did the same thing?!

Further, of the various frameworks used, many will have been created by imposing some further symmetry on the standard theory, in effect decreasing the number of free parameters!

[nonbel]

Can you point out one that was inconsistent with the foundations of physics? I suppose it is possible some were that radical.

[SiempreViernes]

So now you demand that a new theory shouldn't describe what the old theory describes? Just what do you put into the concept of "overfitting"?!