Model never converges when events with multiples winners are observed

[lucasmaystre]

Model never converges when events with multiples winners are observed

[lucasmaystre]

Hi @liampwll ,
thanks for raising this issue, this is a very good observation. I should put this in the documentation eventually.

You can usually fix this by decreasing the learning rate. To do this, when calling the fit() function, you can set the keyword argument lr with a value between 0.0 and 1.0 (default).

Could you try with lr=0.5 or lr=0.2?

Best,
Lucas

[liampwll]

Thanks, 0.2 works well with my dataset and kernels although 0.5 does not.

[lucasmaystre]

Great. I think lr = (1 / n_players) is a good rule of thumb.

When you decrease the learning rate, you might also want to decrease the convergence threshold (tolparameter of the fit function), maybe to 1e-4 or 1e-5.