Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4087#discussion_r26169197
--- Diff: docs/mllib-naive-bayes.md ---
@@ -13,12 +13,15 @@ compute the conditional probability distribution of
label given an observation
and use it for prediction.
MLlib supports [multinomial naive
-Bayes](http://en.wikipedia.org/wiki/Naive_Bayes_classifier#Multinomial_naive_Bayes),
-which is typically used for [document
-classification](http://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html).
+Bayes](http://en.wikipedia.org/wiki/Naive_Bayes_classifier#Multinomial_naive_Bayes)
+and [Bernoulli naive Bayes]
(http://nlp.stanford.edu/IR-book/html/htmledition/the-bernoulli-model-1.html).
+Which are typically used for [document classification]
+(http://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html).
Within that context, each observation is a document and each
-feature represents a term whose value is the frequency of the term.
-Feature values must be nonnegative to represent term frequencies.
+feature represents a term whose value is the frequency of the term (in
multinomial naive Bayes) or
+a zero or one indicating whether the term was found in the document (in
Bernoulli naive Bayes).
+Feature values must be nonnegative.The model type is selected with on
optional parameter
--- End diff --
Space after period.
Also: "on" --> "an"
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