diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md
index 2b2be4d9d0273..8029edca16002 100644
--- a/docs/mllib-linear-methods.md
+++ b/docs/mllib-linear-methods.md
@@ -785,8 +785,7 @@ gradient descent (`stepSize`, `numIterations`, `miniBatchFraction`).  For each o
 all three possible regularizations (none, L1 or L2).
 
 For Logistic Regression, [L-BFGS](api/scala/index.html#org.apache.spark.mllib.optimization.LBFGS)
-version is implemented under [LogisticRegressionWithLBFGS]
-(api/scala/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS), and this
+version is implemented under [LogisticRegressionWithLBFGS](api/scala/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS), and this
 version supports both binary and multinomial Logistic Regression while SGD version only supports
 binary Logistic Regression. However, L-BFGS version doesn't support L1 regularization but SGD one
 supports L1 regularization. When L1 regularization is not required, L-BFGS version is strongly