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| author | Yanbo Liang <ybliang8@gmail.com> | 2016-07-11 14:31:11 -0700 |
|---|---|---|
| committer | Shivaram Venkataraman <shivaram@cs.berkeley.edu> | 2016-07-11 14:31:11 -0700 |
| commit | 2ad031be67c7a0f0c4895c084c891330a9ec935e (patch) | |
| tree | 1972b9f3226ca0026db712b6c32faba47f23b2e1 /R | |
| parent | 840853ed06d63694bf98b21a889a960aac6ac0ac (diff) | |
| download | spark-2ad031be67c7a0f0c4895c084c891330a9ec935e.tar.gz spark-2ad031be67c7a0f0c4895c084c891330a9ec935e.tar.bz2 spark-2ad031be67c7a0f0c4895c084c891330a9ec935e.zip | |
[SPARKR][DOC] SparkR ML user guides update for 2.0
## What changes were proposed in this pull request?
* Update SparkR ML section to make them consistent with SparkR API docs.
* Since #13972 adds labelling support for the ```include_example``` Jekyll plugin, so that we can split the single ```ml.R``` example file into multiple line blocks with different labels, and include them in different algorithms/models in the generated HTML page.
## How was this patch tested?
Only docs update, manually check the generated docs.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #14011 from yanboliang/r-user-guide-update.
Diffstat (limited to 'R')
| -rw-r--r-- | R/pkg/R/mllib.R | 8 |
1 files changed, 5 insertions, 3 deletions
diff --git a/R/pkg/R/mllib.R b/R/pkg/R/mllib.R index 4fe73671f8..e9fd0c75c1 100644 --- a/R/pkg/R/mllib.R +++ b/R/pkg/R/mllib.R @@ -55,8 +55,9 @@ setClass("KMeansModel", representation(jobj = "jobj")) #' Generalized Linear Models #' -#' Fits generalized linear model against a Spark DataFrame. Users can print, make predictions on the -#' produced model and save the model to the input path. +#' Fits generalized linear model against a Spark DataFrame. +#' 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 SparkDataFrame for training. #' @param formula A symbolic description of the model to be fitted. Currently only a few formula @@ -270,7 +271,8 @@ setMethod("summary", signature(object = "NaiveBayesModel"), #' K-Means Clustering Model #' #' Fits a k-means clustering model against a Spark DataFrame, similarly to R's kmeans(). -#' Users can print, make predictions on the produced model and save the model to the input path. +#' 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 SparkDataFrame for training #' @param formula A symbolic description of the model to be fitted. Currently only a few formula |