Describe the workflow you want to enable

Hi everyone,

I am manipulating SVR objects in GridSearcheCV. I am able to access the mean_fit_time in the cv_results_, but I can't access the number of iterations of the optimization problem.

I would like to have this information to properly set the max_iter parameter of the GridSearch.

Describe your proposed solution

I have tried the following:

from sklearn.svm import SVR
from sklearn.datasets import load_boston

# Load data
X, y = load_boston(return_X_y=True)

# Model test
model = SVR(verbose=4)
model.fit(X, y)

[LibSVM]*
optimization finished, #iter = 351
obj = -3012.975812, rho = -21.172739
nSV = 499, nBSV = 431
Out[1]: SVR(gamma=1.0, verbose=4)

I am interested in getting the #iter field here. It should be available as a property of the model once fitted, and all number of iterations should appear somewhere in the cv_results_.

Also, please not that this feature should be available for all libsvm-based SVM objects: SVC, SVR, etc...

Additional context

I am running this code on:
Python 3.7.3
scikit-learn 0.23.1

Thanks by advance for your support.