huaxingao commented on a change in pull request #27593: 
[SPARK-30818][SPARKR][ML] Add SparkR LinearRegression wrapper
URL: https://github.com/apache/spark/pull/27593#discussion_r396690424
 
 

 ##########
 File path: R/pkg/R/mllib_regression.R
 ##########
 @@ -540,3 +546,145 @@ setMethod("write.ml", signature(object = 
"AFTSurvivalRegressionModel", path = "c
           function(object, path, overwrite = FALSE) {
             write_internal(object, path, overwrite)
           })
+
+#' Linear Regression Model
+#'
+#' \code{spark.lm} fits a linear regression model against a SparkDataFrame.
+#' Users can call \code{predict} to make
+#' predictions on new data, and \code{write.ml}/\code{read.ml} to save/load 
fitted models.
+#'
+#' @param data a \code{SparkDataFrame} of observations and labels for model 
fitting.
+#' @param formula a symbolic description of the model to be fitted. Currently 
only a few formula
+#'                operators are supported, including '~', '.', ':', '+', and 
'-'.
+#' @param maxIter maximum iteration number.
+#' @param regParam the regularization parameter.
+#' @param elasticNetParam the ElasticNet mixing parameter, in range [0, 1].
+#'        For alpha = 0, the penalty is an L2 penalty. For alpha = 1, it is an 
L1 penalty.
+#' @param tol convergence tolerance of iterations.
+#' @param standardization whether to standardize the training features before 
fitting the model.
+#' @param weightCol weight column name.
+#' @param aggregationDepth suggested depth for treeAggregate (>= 2).
+#' @param loss the loss function to be optimized. Supported options: 
"squaredError" and "huber"
+#' @param epsilon the shape parameter to control the amount of robustnes
 
 Review comment:
   super nit: ```robustnes``` -> ```robustness```

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