huaxingao commented on a change in pull request #27571:
[SPARK-30819][SPARKR][ML] Add FMRegressor wrapper to SparkR
URL: https://github.com/apache/spark/pull/27571#discussion_r405098967
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File path: R/pkg/R/mllib_regression.R
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@@ -540,3 +546,147 @@ setMethod("write.ml", signature(object =
"AFTSurvivalRegressionModel", path = "c
function(object, path, overwrite = FALSE) {
write_internal(object, path, overwrite)
})
+
+#' Factorization Machines Regression Model
+#'
+#' \code{spark.fmRegressor} fits a factorization regression model against a
SparkDataFrame.
+#' Users can call \code{summary} to print a summary of the fitted model,
\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 factorSize dimensionality of the factors.
+#' @param fitLinear whether to fit linear term. # TODO Can we express this
with formula?
+#' @param regParam the regularization parameter.
+#' @param miniBatchFraction the mini-batch fraction parameter.
+#' @param initStd the standard deviation of initial coefficients.
+#' @param maxIter maximum iteration number.
+#' @param stepSize stepSize parameter.
+#' @param tol convergence tolerance of iterations.
+#' @param solver solver parameter, supported options: "gd" (minibatch gradient
descent) or "adamW".
+#' @param seed seed parameter for weights initialization.
+#' @param stringIndexerOrderType how to order categories of a string feature
column. This is used to
+#' decide the base level of a string feature as
the last category
+#' after ordering is dropped when encoding
strings. Supported options
+#' are "frequencyDesc", "frequencyAsc",
"alphabetDesc", and
+#' "alphabetAsc". The default value is
"frequencyDesc". When the
+#' ordering is set to "alphabetDesc", this drops
the same category
+#' as R when encoding strings.
+#' @param ... additional arguments passed to the method.
+#' @return \code{spark.fmRegressor} returns a fitted Factorization Machines
Regression Model.
+#'
+#' @rdname spark.fmRegressor
+#' @aliases spark.fmRegressor,SparkDataFrame,formula-method
+#' @name spark.fmRegressor
+#' @seealso \link{read.ml}
+#' @examples
+#' \dontrun{
+#' df <- read.df("data/mllib/sample_linear_regression_data.txt", source =
"libsvm")
+#'
+#' # fit Factorization Machines Regression Model
+#' model <- spark.fmRegressor(
+#' df, label ~ features,
Review comment:
nit: The indents seem not right?
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