clarify R

R/pkg/R/mllib_recommendation.R

@@ -49,7 +49,7 @@ setClass("ALSModel", representation(jobj = "jobj"))
 #' @param numItemBlocks number of item blocks used to parallelize computation (> 0).
 #' @param checkpointInterval number of checkpoint intervals (>= 1) or disable checkpoint (-1).
 #'                           Note: this setting will be ignored if the checkpoint directory is not
-#'                           set in the SparkContext.
+#'                           set.
 #' @param ... additional argument(s) passed to the method.
 #' @return \code{spark.als} returns a fitted ALS model.
 #' @rdname spark.als

R/pkg/R/mllib_tree.R

@@ -162,7 +162,7 @@ print.summary.decisionTree <- function(x) {
 #' @param minInfoGain Minimum information gain for a split to be considered at a tree node.
 #' @param checkpointInterval Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
 #'                           Note: this setting will be ignored if the checkpoint directory is not
-#'                           set in the SparkContext.
+#'                           set.
 #' @param maxMemoryInMB Maximum memory in MB allocated to histogram aggregation.
 #' @param cacheNodeIds If FALSE, the algorithm will pass trees to executors to match instances with
 #'                     nodes. If TRUE, the algorithm will cache node IDs for each instance. Caching
@@ -385,7 +385,7 @@ setMethod("write.ml", signature(object = "GBTClassificationModel", path = "chara
 #' @param minInfoGain Minimum information gain for a split to be considered at a tree node.
 #' @param checkpointInterval Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
 #'                           Note: this setting will be ignored if the checkpoint directory is not
-#'                           set in the SparkContext.
+#'                           set.
 #' @param maxMemoryInMB Maximum memory in MB allocated to histogram aggregation.
 #' @param cacheNodeIds If FALSE, the algorithm will pass trees to executors to match instances with
 #'                     nodes. If TRUE, the algorithm will cache node IDs for each instance. Caching
@@ -600,7 +600,7 @@ setMethod("write.ml", signature(object = "RandomForestClassificationModel", path
 #' @param minInfoGain Minimum information gain for a split to be considered at a tree node.
 #' @param checkpointInterval Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
 #'                           Note: this setting will be ignored if the checkpoint directory is not
-#'                           set in the SparkContext.
+#'                           set.
 #' @param maxMemoryInMB Maximum memory in MB allocated to histogram aggregation.
 #' @param cacheNodeIds If FALSE, the algorithm will pass trees to executors to match instances with
 #'                     nodes. If TRUE, the algorithm will cache node IDs for each instance. Caching