From b196056190c569505cc32669d1aec30ed9d70665 Mon Sep 17 00:00:00 2001 From: DB Tsai <dbtsai@alpinenow.com> Date: Mon, 2 Mar 2015 22:37:12 -0800 Subject: [PATCH] [SPARK-5537][MLlib][Docs] Add user guide for multinomial logistic regression Adding more description on top of #4861. Author: DB Tsai <dbtsai@alpinenow.com> Closes #4866 from dbtsai/doc and squashes the following commits: 37e9d07 [DB Tsai] doc --- docs/mllib-linear-methods.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md index 03f90d718a..9270741d43 100644 --- a/docs/mllib-linear-methods.md +++ b/docs/mllib-linear-methods.md @@ -784,9 +784,19 @@ regularization parameter (`regParam`) along with various parameters associated w gradient descent (`stepSize`, `numIterations`, `miniBatchFraction`). For each of them, we support 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 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 +recommended since it converges faster and more accurately compared to SGD by approximating the +inverse Hessian matrix using quasi-Newton method. + Algorithms are all implemented in Scala: * [SVMWithSGD](api/scala/index.html#org.apache.spark.mllib.classification.SVMWithSGD) +* [LogisticRegressionWithLBFGS](api/scala/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS) * [LogisticRegressionWithSGD](api/scala/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithSGD) * [LinearRegressionWithSGD](api/scala/index.html#org.apache.spark.mllib.regression.LinearRegressionWithSGD) * [RidgeRegressionWithSGD](api/scala/index.html#org.apache.spark.mllib.regression.RidgeRegressionWithSGD) -- GitLab