Github user yanboliang commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16148#discussion_r91022054
  
    --- Diff: docs/sparkr.md ---
    @@ -512,39 +512,33 @@ head(teenagers)
     
     # Machine Learning
     
    -SparkR supports the following machine learning algorithms currently: 
`Generalized Linear Model`, `Accelerated Failure Time (AFT) Survival Regression 
Model`, `Naive Bayes Model` and `KMeans Model`.
    -Under the hood, SparkR uses MLlib to train the model.
    -Users can call `summary` to print a summary of the fitted model, 
[predict](api/R/predict.html) to make predictions on new data, and 
[write.ml](api/R/write.ml.html)/[read.ml](api/R/read.ml.html) to save/load 
fitted models.
    -SparkR supports a subset of the available R formula operators for model 
fitting, including ‘~’, ‘.’, ‘:’, ‘+’, and ‘-‘.
    -
     ## Algorithms
     
    -### Generalized Linear Model
    -
    -[spark.glm()](api/R/spark.glm.html) or [glm()](api/R/glm.html) fits 
generalized linear model against a Spark DataFrame.
    -Currently "gaussian", "binomial", "poisson" and "gamma" families are 
supported.
    -{% include_example glm r/ml.R %}
    -
    -### Accelerated Failure Time (AFT) Survival Regression Model
    -
    -[spark.survreg()](api/R/spark.survreg.html) fits an accelerated failure 
time (AFT) survival regression model on a SparkDataFrame.
    -Note that the formula of [spark.survreg()](api/R/spark.survreg.html) does 
not support operator '.' currently.
    --- End diff --
    
    Ditto, can be found at R API doc.


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