Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8436#discussion_r38146311
--- Diff: docs/ml-features.md ---
@@ -306,16 +306,88 @@ regexTokenizer = RegexTokenizer(inputCol="sentence",
outputCol="words", pattern=
</div>
</div>
+## StopWordsRemover
+[Stop words](https://en.wikipedia.org/wiki/Stop_words) are words which
+should be excluded from the input, typically because the words appear
+frequently and don't carry as much meaning.
+
+`StopWordsRemover` takes as input a sequence of strings (e.g. the output
+of a [Tokenizer](ml-features.html#tokenizer)) and drops all the stop
+words from the input sequences. The list of stopwords is specified by
+the `stopWords` parameter. We provide a list of stop words created by
+the [Glasgow Information Retrieval
+Group](http://ir.dcs.gla.ac.uk/resources/linguistic_utils/stop_words) in
+`StopWords.EnglishStopWords`, which is used by default.
+
+<div class="codetabs">
+
+<div data-lang="scala" markdown="1">
+
+[`StopWordsRemover`](api/scala/index.html#org.apache.spark.ml.feature.StopWordsRemover)
+takes an input column name, an output column name, a list of stop words,
+and a boolean indicating if the matches should be case sensitive (false
+by default).
+
+{% highlight scala %}
+import org.apache.spark.ml.feature.StopWordsRemover
+
+val remover = new StopWordsRemover()
+ .setInputCol("raw")
+ .setOutputCol("filtered")
+val dataSet = sqlContext.createDataFrame(Seq(
+ (Seq("I", "saw", "the", "red", "baloon")),
+ (Seq("Mary", "had", "a", "little", "lamb"))
+).map(Tuple1.apply)).toDF("raw")
+
+remover.transform(dataSet).show()
--- End diff --
It is useful to show the result, as in the user guide of `StringIndexer`.
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