Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/14558#discussion_r74693197
--- Diff: R/pkg/R/generics.R ---
@@ -1251,10 +1311,57 @@ setGeneric("year", function(x) {
standardGeneric("year") })
#' @export
setGeneric("spark.glm", function(data, formula, ...) {
standardGeneric("spark.glm") })
+#' @param formula a symbolic description of the model to be fitted. If
\code{data} is a
+#' SparkDataFrame, currently only a few formula operators
are supported,
+#' including '~', '.', ':', '+', and '-'.
+#' @param data a SparkDataFrame or (R glm) data.frame, list or environment
for training.
+#' @param family a description of the error distribution and link function
to be used in the model.
+#' This can be a character string naming a family function,
a family function or
+#' the result of a call to a family function. Refer R family
at
+#'
\url{https://stat.ethz.ch/R-manual/R-devel/library/stats/html/family.html}.
+#' @param epsilon positive convergence tolerance of iterations.
+#' @param maxit integer giving the maximal number of IRLS iterations.
+#' @param weights an optional vector of 'prior weights' to be used in the
fitting process.
+#' Should be NULL or a numeric vector.
+#' @param subset an optional vector specifying a subset of observations to
be used in the
+#' fitting process.
+#' @param na.action a function which indicates what should happen when the
data contain NAs.
+#' The default is set by the na.action setting of
options, and is na.fail
+#' if that is unset. The 'factory-fresh' default is
na.omit. Another possible
+#' value is NULL, no action. Value na.exclude can be
useful.
+#' @param start starting values for the parameters in the linear predictor.
+#' @param etastart starting values for the linear predictor.
+#' @param mustart starting values for the vector of means.
+#' @param offset this can be used to specify an a priori known component
to be included in
+#' the linear predictor during fitting. This should be NULL
or
+#' a numeric vector of length equal to the number of cases.
One or more offset
+#' terms can be included in the formula instead or as well,
and if more than
+#' one is specified their sum is used. See model.offset.
+#' @param control a list of parameters for controlling the fitting
process. For glm.fit
+#' this is passed to glm.control.
+#' @param model a logical value indicating whether model frame should be
included as
+#' a component of the returned value.
+#' @param method the method to be used in fitting the model. The default
method
+#' "glm.fit" uses iteratively reweighted least squares
(IWLS): the alternative
+#' "model.frame" returns the model frame and does no fitting.
+#' User-supplied fitting functions can be supplied either as
a function or
+#' a character string naming a function, with a function
which takes the same
+#' arguments as glm.fit. If specified as a character string
it is looked up from
+#' within the stats namespace.
+#' @param x,y logical values indicating whether the response vector and
model matrix
+#' used in the fitting process should be returned as components
of the returned value.
+#' @param contrasts an optional list. See the contrasts.arg of
model.matrix.default.
+#' @param ... arguments to be used to form the default control
argument if it is
+#' not supplied directly.
#' @rdname glm
+#' @details If \code{data} is a data.frame, list or environment,
\code{glm} behaves the same as
+#' \code{glm} in the \code{stats} package. If \code{data} is a
SparkDataFrame,
+#' \code{spark.glm} is called.
#' @export
setGeneric("glm")
+#' @param object a fitted ML model object.
+#' @param ... additional argument(s) passed to the method.
--- End diff --
`Currently not used` - we don't use this in any `predict` implementation
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