Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4709#discussion_r25113936
--- Diff: docs/mllib-feature-extraction.md ---
@@ -375,3 +375,28 @@ data2 = labels.zip(normalizer2.transform(features))
{% endhighlight %}
</div>
</div>
+
+## Feature selection
+Feature selection allows selecting relevant features for use in model
construction leaving out the redundant ones. The number of features to select
can be determined using the validation set. Feature selection is usually
applied on sparse data, for example in text classification. Feature selection
reduces the size of the vector space and, in turn, the complexity of any
subsequent operation with vectors.
--- End diff --
Would you mind adding a link to Wikipedia?
[http://en.wikipedia.org/wiki/Feature_selection]
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