Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/13176#discussion_r67237898
--- Diff: docs/ml-features.md ---
@@ -46,14 +46,16 @@ In MLlib, we separate TF and IDF to make them flexible.
`HashingTF` is a `Transformer` which takes sets of terms and converts
those sets into
fixed-length feature vectors. In text processing, a "set of terms" might
be a bag of words.
`HashingTF` utilizes the [hashing
trick](http://en.wikipedia.org/wiki/Feature_hashing).
-A raw feature is mapped into an index (term) by applying a hash function.
Then term frequencies
+A raw feature is mapped into an index (term) by applying a hash function.
The hash function used here is [MurmurHash
3](https://en.wikipedia.org/wiki/MurmurHash).Then term frequencies
--- End diff --
Put space between sentences
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