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Diffstat (limited to 'docs/mllib-linear-methods.md')
| -rw-r--r-- | docs/mllib-linear-methods.md | 3 |
1 files changed, 1 insertions, 2 deletions
diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md index 2b2be4d9d0..8029edca16 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 |