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From m...@apache.org
Subject svn commit: r1723237 - in /spark: mllib/index.md site/mllib/index.html site/news/index.html
Date Wed, 06 Jan 2016 06:27:47 GMT
Author: meng
Date: Wed Jan  6 06:27:47 2016
New Revision: 1723237

URL: http://svn.apache.org/viewvc?rev=1723237&view=rev
Log:
list bisecting k-means and AFT regression on mllib page

Modified:
    spark/mllib/index.md
    spark/site/mllib/index.html
    spark/site/news/index.html

Modified: spark/mllib/index.md
URL: http://svn.apache.org/viewvc/spark/mllib/index.md?rev=1723237&r1=1723236&r2=1723237&view=diff
==============================================================================
--- spark/mllib/index.md (original)
+++ spark/mllib/index.md Wed Jan  6 06:27:47 2016
@@ -90,8 +90,9 @@ subproject: MLlib
       <li>classification and regression tree</li>
       <li>random forest and gradient-boosted trees</li>
       <li>recommendation via alternating least squares (ALS)</li>
-      <li>clustering via k-means, Gaussian mixtures (GMM), and power iteration clustering</li>
+      <li>clustering via k-means, bisecting k-means, Gaussian mixtures (GMM), and power
iteration clustering</li>
       <li>topic modeling via latent Dirichlet allocation (LDA)</li>
+      <li>survival analysis via accelerated failure time model</li>
       <li>singular value decomposition (SVD) and QR decomposition</li>
       <li>principal component analysis (PCA)</li>
       <li>linear regression with L<sub>1</sub>, L<sub>2</sub>,
and elastic-net regularization</li>

Modified: spark/site/mllib/index.html
URL: http://svn.apache.org/viewvc/spark/site/mllib/index.html?rev=1723237&r1=1723236&r2=1723237&view=diff
==============================================================================
--- spark/site/mllib/index.html (original)
+++ spark/site/mllib/index.html Wed Jan  6 06:27:47 2016
@@ -257,8 +257,9 @@
       <li>classification and regression tree</li>
       <li>random forest and gradient-boosted trees</li>
       <li>recommendation via alternating least squares (ALS)</li>
-      <li>clustering via k-means, Gaussian mixtures (GMM), and power iteration clustering</li>
+      <li>clustering via k-means, bisecting k-means, Gaussian mixtures (GMM), and power
iteration clustering</li>
       <li>topic modeling via latent Dirichlet allocation (LDA)</li>
+      <li>survival analysis via accelerated failure time model</li>
       <li>singular value decomposition (SVD) and QR decomposition</li>
       <li>principal component analysis (PCA)</li>
       <li>linear regression with L<sub>1</sub>, L<sub>2</sub>,
and elastic-net regularization</li>

Modified: spark/site/news/index.html
URL: http://svn.apache.org/viewvc/spark/site/news/index.html?rev=1723237&r1=1723236&r2=1723237&view=diff
==============================================================================
--- spark/site/news/index.html (original)
+++ spark/site/news/index.html Wed Jan  6 06:27:47 2016
@@ -275,7 +275,7 @@ With this release the Spark community co
 <article class="hentry">
     <header class="entry-header">
       <h3 class="entry-title"><a href="/news/one-month-to-spark-summit-2015.html">One
month to Spark Summit 2015 in San Francisco</a></h3>
-      <div class="entry-date">May 15, 2015</div>
+      <div class="entry-date">May 16, 2015</div>
     </header>
     <div class="entry-content"><p>There is one month left until <a href="https://spark-summit.org/2015/">Spark
Summit 2015</a>, which
 will be held in San Francisco on June 15th to 17th.
@@ -287,7 +287,7 @@ The Summit will contain <a href="https:/
 <article class="hentry">
     <header class="entry-header">
       <h3 class="entry-title"><a href="/news/spark-summit-europe.html">Announcing
Spark Summit Europe</a></h3>
-      <div class="entry-date">May 15, 2015</div>
+      <div class="entry-date">May 16, 2015</div>
     </header>
     <div class="entry-content"><p>Abstract submissions are now open for the first
ever <a href="https://www.prevalentdesignevents.com/sparksummit2015/europe/speaker/">Spark
Summit Europe</a>. The event will take place on October 27th to 29th in Amsterdam. Submissions
are welcome across a variety of Spark related topics, including use cases and ongoing development.</p>
 



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