Linear model throws convergence error on city_rev.csv

[bchen1116]

Preview of the error:

We've noticed this for several of our perf testing datasets. One in particular was regress.csv Cloudwatch link here The warning being printed:

2021-09-09T17:33:44.934-04:00 | //.pyenv/versions/3.8.3/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:763: ConvergenceWarning: lbfgs failed to converge (status=1):
-- | --
  | 2021-09-09T17:33:44.934-04:00 | STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.
  | 2021-09-09T17:33:44.934-04:00 | Increase the number of iterations (max_iter) or scale the data as shown in:
  | 2021-09-09T17:33:44.934-04:00 | https://scikit-learn.org/stable/modules/preprocessing.html
  | 2021-09-09T17:33:44.934-04:00 | Please also refer to the documentation for alternative solver options:
  | 2021-09-09T17:33:44.934-04:00 | https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  | 2021-09-09T17:33:44.934-04:00 | n_iter_i = _check_optimize_result(

This could be in relation to the Elastic Net models we have.

[dsherry]

@ParthivNaresh noticed that we're getting a similar but slightly different message for sktime. "Could not optimize". He's gonna file a separate issue for that.