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DOC change logreg solver in plot_logistic_path #15927

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Merged
merged 2 commits into from
Dec 23, 2019
Merged

DOC change logreg solver in plot_logistic_path #15927

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933e1a1
change logreg solver in plot_logistic_path
agramfort Dec 19, 2019
62e9fc9
remove ref to SAGA
agramfort Dec 21, 2019
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7 changes: 4 additions & 3 deletions examples/linear_model/plot_logistic_path.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@
coefficients are exactly 0. When regularization gets progressively looser,
coefficients can get non-zero values one after the other.

Here we choose the SAGA solver because it can efficiently optimize for the
Here we choose the liblinear solver because it can efficiently optimize for the
Logistic Regression loss with a non-smooth, sparsity inducing l1 penalty.

Also note that we set a low value for the tolerance to make sure that the model
Expand Down Expand Up @@ -55,9 +55,10 @@

print("Computing regularization path ...")
start = time()
clf = linear_model.LogisticRegression(penalty='l1', solver='saga',
clf = linear_model.LogisticRegression(penalty='l1', solver='liblinear',
tol=1e-6, max_iter=int(1e6),
warm_start=True)
warm_start=True,
intercept_scaling=10000.)
coefs_ = []
for c in cs:
clf.set_params(C=c)
Expand Down