Github user thunterdb commented on a diff in the pull request:
https://github.com/apache/spark/pull/11549#discussion_r56907102
--- Diff: R/pkg/R/mllib.R ---
@@ -29,15 +29,10 @@ setClass("PipelineModel", representation(model =
"jobj"))
#' @param formula A symbolic description of the model to be fitted.
Currently only a few formula
#' operators are supported, including '~', '.', ':', '+',
and '-'.
#' @param data DataFrame for training
-#' @param family Error distribution. "gaussian" -> linear regression,
"binomial" -> logistic reg.
+#' @param family a description of the error distribution and link function
to be used in the model,
+#' as in
[[https://stat.ethz.ch/R-manual/R-devel/library/stats/html/family.html]]
#' @param lambda Regularization parameter
-#' @param alpha Elastic-net mixing parameter (see glmnet's documentation
for details)
-#' @param standardize Whether to standardize features before training
-#' @param solver The solver algorithm used for optimization, this can be
"l-bfgs", "normal" and
-#' "auto". "l-bfgs" denotes Limited-memory BFGS which is a
limited-memory
-#' quasi-Newton optimization method. "normal" denotes using
Normal Equation as an
-#' analytical solution to the linear regression problem. The
default value is "auto"
-#' which means that the solver algorithm is selected
automatically.
+#' @param solver Currently only support "irls" which is also the default
solver.
--- End diff --
The previous comment was more explicit, especially with respect to 'auto'
(the default). It should mention auto and irls as the two options.
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