[Review] Improve warning message when QN solver reaches max_iter

[tfeher]

closes #2546

This PR improves the warning message printed when max iterations are reached during fitting a linear model.

Example:

import numpy as np
from cuml.linear_model import LogisticRegression
from sklearn.datasets import load_breast_cancer
X, y = load_breast_cancer(return_X_y=True)
y = y.astype(np.float64)
cls = LogisticRegression(penalty='none', C=1)
cls.fit(X, y)

This produces the following output, where the last line is added by this PR:

[W] [15:31:04.467478] L-BFGS: max iterations reached
[W] [15:31:04.467804] Maximum iterations reached before solver is converged. To increase model accuracy you can increase the number of iterations (max_iter) or improve the scaling of the input data.

[dantegd]

lgtm

[dantegd]

rerun tests

[codecov-io]

Codecov Report

Merging #3515 (ab6b917) into branch-0.19 (39c7262) will increase coverage by 7.58%.
The diff coverage is 71.72%.

@@               Coverage Diff               @@
##           branch-0.19    #3515      +/-   ##
===============================================
+ Coverage        71.77%   79.36%   +7.58%     
===============================================
  Files              212      225      +13     
  Lines            17075    17946     +871     
===============================================
+ Hits             12256    14243    +1987     
+ Misses            4819     3703    -1116     

Flag	Coverage Δ
dask	44.12% <14.67%> (?)
non-dask	71.65% <69.97%> (?)

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
...on/cuml/_thirdparty/sklearn/preprocessing/_data.py	63.61% <ø> (+0.07%)	⬆️
python/cuml/experimental/explainer/common.py	88.05% <42.85%> (-4.01%)	⬇️
...l/_thirdparty/sklearn/preprocessing/_imputation.py	62.40% <50.00%> (-0.11%)	⬇️
python/cuml/neighbors/nearest_neighbors.pyx	92.43% <50.00%> (-0.29%)	⬇️
python/cuml/neighbors/ann.pyx	61.62% <61.62%> (ø)
python/cuml/common/import_utils.py	59.43% <66.66%> (+3.43%)	⬆️
python/cuml/experimental/explainer/base.pyx	67.06% <67.06%> (ø)
python/cuml/dask/common/utils.py	43.68% <83.33%> (+16.13%)	⬆️
python/cuml/experimental/explainer/kernel_shap.pyx	97.75% <100.00%> (+0.48%)	⬆️
...n/cuml/experimental/explainer/permutation_shap.pyx	98.82% <100.00%> (+0.84%)	⬆️
... and 69 more

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[dantegd]

@gpucibot merge