Clarify effect of enable_categorical

R-package/R/xgb.DMatrix.R

@@ -27,14 +27,24 @@
 #' @param label_lower_bound Lower bound for survival training.
 #' @param label_upper_bound Upper bound for survival training.
 #' @param feature_weights Set feature weights for column sampling.
+#' @param enable_categorical Experimental support of specializing for categorical features.
+#'
+#'                           If passing 'TRUE' and 'data' is a data frame,
+#'                           columns of categorical types will automatically
+#'                           be set to be of categorical type (feature_type='c') in the resulting DMatrix.
+#'
+#'                           If passing 'FALSE' and 'data' is a data frame with categorical columns,
+#'                           it will result in an error being thrown.
+#'
+#'                           If 'data' is not a data frame, this argument is ignored.
+#'
+#'                           JSON/UBJSON serialization format is required for this.
 #'
 #' @details
 #' Note that DMatrix objects are not serializable through R functions such as \code{saveRDS} or \code{save}.
 #' If a DMatrix gets serialized and then de-serialized (for example, when saving data in an R session or caching
 #' chunks in an Rmd file), the resulting object will not be usable anymore and will need to be reconstructed
 #' from the original source of data.
-#' @param enable_categorical Experimental support of specializing for
-#'        categorical features. JSON/UBJSON serialization format is required.
 #'
 #' @examples
 #' data(agaricus.train, package='xgboost')

python-package/xgboost/core.py

@@ -822,8 +822,18 @@ def __init__(
 
             .. note:: This parameter is experimental
 
-            Experimental support of specializing for categorical features. JSON/UBJSON
-            serialization format is required.
+            Experimental support of specializing for categorical features.
+
+            If passing 'True' and 'data' is a data frame (from supported libraries
+            such as Pandas or Modin), columns of categorical types will automatically
+            be set to be of categorical type (feature_type='c') in the resulting DMatrix.
+
+            If passing 'False' and 'data' is a data frame with categorical columns,
+            it will result in an error being thrown.
+
+            If 'data' is not a data frame, this argument is ignored.
+
+            JSON/UBJSON serialization format is required for this.
 
         """
         if group is not None and qid is not None: