How to increase iterations?

[RicardoFCJ]

I'm trying to train the models but it is not converging. I tried to set max_iter in regressor, but it is not recognizing it. This is the warning I'm getting.

ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 0.17428639502685428, tolerance: 0.0699999999999999

Should I just wait for it to finish, or, if not, how can I increase iterations?

[natekupp]

Hey @RicardoFCJ - I've seen this a bunch in the past but have never had a chance to debug what's going on. If you have time would love to hear what you learn.

If you grep the codebase for max_iter you can see it's hard-coded to 5000 right now; it may be worth experimenting with that. Also it should certainly not be hard-coded :)

[RicardoFCJ]

I'm sorry for the delayed response.
(I'm not sure if that's what you're asking with "would love to hear what you learn", but ...)
What I'm trying to learn is a dataset precision agriculture with 50 features and ~700 cases.

[maxiimilian]

I am reviving this, because I have problems with it aswell. If the duality gap is too large, results are really not so good because the optimization did not converge.

A manual fix is to increase max_iter in ffx/core/model_factories.py inside the _pathwiseLearn() function (l. 414).

However, I was thinking of a more permanent solution. Since **fit_params get's passed to _pathwiseLearn() anyway, we could use that dict to drag along max_iter from run() and from the constructor of the FFXRegressor. That would be a bit ugly and difficult to test so I am open to better suggestions.