Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/11486#discussion_r56258707
--- Diff: R/pkg/R/generics.R ---
@@ -1168,3 +1168,7 @@ setGeneric("kmeans")
#' @rdname fitted
#' @export
setGeneric("fitted")
+
+#' @rdname naiveBayes
+#' @export
+setGeneric("naiveBayes", function(formula, data, ...) {
standardGeneric("naiveBayes") })
--- End diff --
Users need `e1071::naiveBayes` to call that. Both `naiveBayes` are
implemented as S3 generic functions and the Spark one shares the same first
argument type (`formula`) with the one in e1071. So I don't think we can avoid
shadowing the method. I tried different loading orders and confirmed that both
can be used with namespace prefixes.
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