Repository: spark
Updated Branches:
  refs/heads/branch-1.4 42070f096 -> dfd905df5


[DOCS] [MLLIB] Fixing misformatted links in v1.4 MLlib Naive Bayes 
documentation by removing space and newline characters.

A couple of links in the MLlib Naive Bayes documentation for v1.4 were broken 
due to the addition of either space or newline characters between the link 
title and link URL in the markdown doc.  (Interestingly enough, they are 
rendered correctly in the GitHub viewer, but not when compiled to HTML by 
Jekyll.)

Author: Mike Dusenberry <dusenberr...@gmail.com>

Closes #6412 from dusenberrymw/Fix_Broken_Links_In_MLlib_Naive_Bayes_Docs and 
squashes the following commits:

91a4028 [Mike Dusenberry] Fixing misformatted links by removing space and 
newline characters.

(cherry picked from commit e5a63a0e39e35ba5f6b1732e09128c30fff17a2c)
Signed-off-by: Sean Owen <so...@cloudera.com>


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/dfd905df
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/dfd905df
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/dfd905df

Branch: refs/heads/branch-1.4
Commit: dfd905df5f88996fdc9520068846c1ca40b239d0
Parents: 42070f0
Author: Mike Dusenberry <dusenberr...@gmail.com>
Authored: Tue May 26 17:05:58 2015 +0100
Committer: Sean Owen <so...@cloudera.com>
Committed: Tue May 26 17:06:35 2015 +0100

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 docs/mllib-naive-bayes.md | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/dfd905df/docs/mllib-naive-bayes.md
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diff --git a/docs/mllib-naive-bayes.md b/docs/mllib-naive-bayes.md
index 56a2e9c..acdcc37 100644
--- a/docs/mllib-naive-bayes.md
+++ b/docs/mllib-naive-bayes.md
@@ -14,9 +14,8 @@ and use it for prediction.
 
 MLlib supports [multinomial naive
 
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).
-These models are typically used for [document classification]
-(http://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html).
+and [Bernoulli naive 
Bayes](http://nlp.stanford.edu/IR-book/html/htmledition/the-bernoulli-model-1.html).
+These models 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 (in 
multinomial naive Bayes) or
 a zero or one indicating whether the term was found in the document (in 
Bernoulli naive Bayes).


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