ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.

When I run the following code:
```

from sklearn.ensemble import GradientBoostingRegressor
from sklearn.kernel_approximation import Nystroem
from sklearn.linear_model import ElasticNetCV, RidgeCV
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsRegressor
from sklearn.pipeline import make_pipeline, make_union
from sklearn.svm import LinearSVR
from tpot.builtins import StackingEstimator
from xgboost import XGBRegressor

# Average CV score on the training set was:-0.21141374399237495
exported_pipeline = make_pipeline(
StackingEstimator(estimator=GradientBoostingRegressor(alpha=0.8,
learning_rate=1.0,
loss="quantile",
max_depth=8,
max_features=0.7000000000000001,
min_samples_leaf=16,
min_samples_split=5,
n_estimators=100,
subsample=0.6500000000000001)),
StackingEstimator(estimator=XGBRegressor(learning_rate=0.01,
max_depth=5,
min_child_weight=10,
n_estimators=500,
nthread=1,
subsample=0.55)),
StackingEstimator(estimator=LinearSVR(C=1.0,
dual=True,
epsilon=0.1,
loss="epsilon_insensitive",
tol=0.01)),
StackingEstimator(estimator=RidgeCV()),
StackingEstimator(estimator=LinearSVR(C=20.0,
dual=True,
epsilon=0.0001,
loss="epsilon_insensitive",
tol=0.001)),
Nystroem(gamma=0.15000000000000002,
kernel="laplacian",
n_components=6),
StackingEstimator(estimator=ElasticNetCV(l1_ratio=0.05,
tol=0.01)),
KNeighborsRegressor(n_neighbors=91,
p=2,
weights="distance")
)
exported_pipeline.fit(X_train, y_train)
score = exported_pipeline.score(X_test, y_test)
print('\nScore: ', score)
```
I get:

`ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.`

Any help in making this warning message go away will be greatly appreciated.

Charles