Make convergence warnings appear when verbose = 0 in Logistic Regression.

AlexandreSev · AlexandreSev · commit af76e3632c0c · 2018-03-28T14:19:30.000+02:00
For lbfgs and liblinears solvers, the convergence warnings appeared only when verbose was greater than 0, whereas they appeared with verbose = 0 with other solvers. See scikit-learn#10866
diff --git a/sklearn/linear_model/logistic.py b/sklearn/linear_model/logistic.py
@@ -707,7 +707,7 @@ def logistic_regression_path(X, y, pos_class=None, Cs=10, fit_intercept=True,
                 func, w0, fprime=None,
                 args=(X, target, 1. / C, sample_weight),
                 iprint=(verbose > 0) - 1, pgtol=tol, maxiter=max_iter)
-            if info["warnflag"] == 1 and verbose > 0:
+            if info["warnflag"] == 1:
                 warnings.warn("lbfgs failed to converge. Increase the number "
                               "of iterations.", ConvergenceWarning)
             # In scipy <= 1.0.0, nit may exceed maxiter.
diff --git a/sklearn/svm/base.py b/sklearn/svm/base.py
@@ -907,7 +907,7 @@ def _fit_liblinear(X, y, C, fit_intercept, intercept_scaling, class_weight,
     # on 32-bit platforms, we can't get to the UINT_MAX limit that
     # srand supports
     n_iter_ = max(n_iter_)
-    if n_iter_ >= max_iter and verbose > 0:
+    if n_iter_ >= max_iter:
         warnings.warn("Liblinear failed to converge, increase "
                       "the number of iterations.", ConvergenceWarning)
 
