Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/15365#discussion_r82528616
--- Diff: R/pkg/R/mllib.R ---
@@ -647,6 +654,195 @@ setMethod("predict", signature(object =
"KMeansModel"),
predict_internal(object, newData)
})
+#' Logistic Regression Model
+#'
+#' Fits an logistic regression model against a Spark DataFrame. It
supports "binomial": Binary logistic regression
+#' with pivoting; "multinomial": Multinomial logistic (softmax) regression
without pivoting, similar to glmnet.
+#' Users can print, make predictions on the produced model and save the
model to the input path.
+#'
+#' @param data SparkDataFrame for training
+#' @param formula A symbolic description of the model to be fitted.
Currently only a few formula
+#' operators are supported, including '~', '.', ':', '+',
and '-'.
+#' @param regParam the regularization parameter. Default is 0.0.
+#' @param elasticNetParam the ElasticNet mixing parameter. For alpha = 0,
the penalty is an L2 penalty.
+#' For alpha = 1, it is an L1 penalty. For 0 <
alpha < 1, the penalty is a combination
+#' of L1 and L2. Default is 0.0 which is an L2
penalty.
+#' @param maxIter maximum iteration number.
+#' @param tol convergence tolerance of iterations.
+#' @param fitIntercept whether to fit an intercept term. Default is TRUE.
+#' @param family the name of family which is a description of the label
distribution to be used in the model.
+#' Supported options:
--- End diff --
roxygen2 is going to trim all the whitespaces, you will need to add
formatting with \item and so on
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