Github user atalwalkar commented on a diff in the pull request:
https://github.com/apache/spark/pull/2061#discussion_r16501062
--- Diff: docs/mllib-feature-extraction.md ---
@@ -7,9 +7,87 @@ displayTitle: <a href="mllib-guide.html">MLlib</a> -
Feature Extraction
* Table of contents
{:toc}
+
+## TF-IDF
+
+[Term frequency-inverse document frequency
(TF-IDF)](http://en.wikipedia.org/wiki/Tf%E2%80%93idf) is a feature
+vectorization method widely used in text mining to reflect the importance
of a term to a document in the corpus.
+Denote a term by `$t$`, a document by `$d$`, and the corpus by `$D$`.
+Term frequency `$TF(t, d)$` is the number of times that term `$t$` appears
in document `$d$`.
+And document frequency `$DF(t, D)$` is the number of documents that
contains term `$t$`.
--- End diff --
"...`$d$`. And..." -> "...`$d$`, while..."
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