http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/algorithms/regression/fittness-tests.html
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diff --git a/docs/latest/algorithms/regression/fittness-tests.html 
b/docs/latest/algorithms/regression/fittness-tests.html
index 232ec7e..fffa770 100644
--- a/docs/latest/algorithms/regression/fittness-tests.html
+++ b/docs/latest/algorithms/regression/fittness-tests.html
@@ -185,7 +185,7 @@ Stub</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/algorithms/regression/index.html
----------------------------------------------------------------------
diff --git a/docs/latest/algorithms/regression/index.html 
b/docs/latest/algorithms/regression/index.html
index 6033c4b..78f2f31 100644
--- a/docs/latest/algorithms/regression/index.html
+++ b/docs/latest/algorithms/regression/index.html
@@ -191,7 +191,7 @@
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/algorithms/regression/ols.html
----------------------------------------------------------------------
diff --git a/docs/latest/algorithms/regression/ols.html 
b/docs/latest/algorithms/regression/ols.html
index 41414ea..04b7264 100644
--- a/docs/latest/algorithms/regression/ols.html
+++ b/docs/latest/algorithms/regression/ols.html
@@ -191,12 +191,12 @@ This is in stark contrast to many “big data machine 
learning” frameworks whi
      </tr>
      <tr>
         <td><code>'calcStandardErrors</code></td>
-        <td>Calculate the standard errors (and subsequent "t-scores" and 
"p-values") of the $$\boldsymbol{\beta}$$ estimates</td>
+        <td>Calculate the standard errors (and subsequent "t-scores" and 
"p-values") of the \(\boldsymbol{\beta}\) estimates</td>
         <td><code>true</code></td>
      </tr>
      <tr>
         <td><code>'addIntercept</code></td>
-        <td>Add an intercept to $$\mathbf{X}$$</td>
+        <td>Add an intercept to \(\mathbf{X}\)</td>
         <td><code>true</code></td>
      </tr>                 
   </table>
@@ -237,7 +237,7 @@ This is in stark contrast to many “big data machine 
learning” frameworks whi
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/algorithms/regression/serial-correlation/cochrane-orcutt.html
----------------------------------------------------------------------
diff --git 
a/docs/latest/algorithms/regression/serial-correlation/cochrane-orcutt.html 
b/docs/latest/algorithms/regression/serial-correlation/cochrane-orcutt.html
index 3547b50..6a7470d 100644
--- a/docs/latest/algorithms/regression/serial-correlation/cochrane-orcutt.html
+++ b/docs/latest/algorithms/regression/serial-correlation/cochrane-orcutt.html
@@ -217,7 +217,7 @@ coch = cochrane.orcutt(my_lm)
 <p>Steps:</p>
 <ol>
   <li>Normal Regression</li>
-  <li>Estimate <foo>$$\rho$$</foo></li>
+  <li>Estimate <foo>\(\rho\)</foo></li>
   <li>Get Estimates of Transformed Equation</li>
   <li>Step 5: Use Betas from (4) to recalculate model from (1)</li>
   <li>Step 6: repeat  Step 2 through 5 until a stopping criteria is met. Some 
models call for convergence-
@@ -229,13 +229,13 @@ Kunter et. al reccomend 3 iterations, if you don’t 
achieve desired results, us
 
 <ol>
   <li>“Cochrane-Orcutt does not always work properly.  A major reason is 
that when the error terms
- are positively autocorrelated, the estimate <foo>$$r$$</foo> in (12.22) tends 
to underestimate the autocorrelation
- parameter <foo>$$\rho$$</foo>.  When this bias is serious, it can 
significantly reduce the effectiveness of the
+ are positively autocorrelated, the estimate <foo>\(r\)</foo> in (12.22) tends 
to underestimate the autocorrelation
+ parameter <foo>\(\rho\)</foo>.  When this bias is serious, it can 
significantly reduce the effectiveness of the
  Cochrane-Orcutt approach.</li>
-  <li>“There exists an approximate relation between the <a 
href="dw-test.html">Durbin Watson test statistic</a> <foo>$$\mathbf{D}$$</foo> 
in (12.14)
- and the estimated autocorrelation paramater <foo>$$r$$</foo> in (12.22):</li>
+  <li>“There exists an approximate relation between the <a 
href="dw-test.html">Durbin Watson test statistic</a> <foo>\(\mathbf{D}\)</foo> 
in (12.14)
+ and the estimated autocorrelation paramater <foo>\(r\)</foo> in (12.22):</li>
 </ol>
-<center>$$D ~= 2(1-\rho)$$</center>
+<center>\(D ~= 2(1-\rho)\)</center>
 
 <p>They also note on p492:
  “… If the process does not terminate after one or two iterations, a 
different procedure
@@ -319,7 +319,7 @@ println(coModel.summary)
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/algorithms/regression/serial-correlation/dw-test.html
----------------------------------------------------------------------
diff --git a/docs/latest/algorithms/regression/serial-correlation/dw-test.html 
b/docs/latest/algorithms/regression/serial-correlation/dw-test.html
index 4c29515..3ba53ff 100644
--- a/docs/latest/algorithms/regression/serial-correlation/dw-test.html
+++ b/docs/latest/algorithms/regression/serial-correlation/dw-test.html
@@ -168,19 +168,19 @@
       <h3 id="about">About</h3>
 
 <p>The <a 
href="https://en.wikipedia.org/wiki/Durbin%E2%80%93Watson_statistic";>Durbin 
Watson Test</a> is a test for serial correlation
-in error terms.  The Durbin Watson test statistic <foo>$$d$$</foo> can take 
values between 0 and 4, and in general</p>
+in error terms.  The Durbin Watson test statistic <foo>\(d\)</foo> can take 
values between 0 and 4, and in general</p>
 
 <ul>
   <li>
-    <foo>$$d \lt 1.5 $$</foo>
+    <foo>\(d \lt 1.5 \)</foo>
     <p>implies positive autocorrelation</p>
   </li>
   <li>
-    <foo>$$d \gt 2.5 $$</foo>
+    <foo>\(d \gt 2.5 \)</foo>
     <p>implies negative autocorrelation</p>
   </li>
   <li>
-    <foo>$$1.5 \lt d \lt 2.5 $$</foo>
+    <foo>\(1.5 \lt d \lt 2.5 \)</foo>
     <p>implies to autocorrelation.</p>
   </li>
 </ul>
@@ -226,7 +226,7 @@ val myAnswer: Double = 
model.testResults.getOrElse('durbinWatsonTestStatistic, -
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/algorithms/template.html
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diff --git a/docs/latest/algorithms/template.html 
b/docs/latest/algorithms/template.html
index d032117..87ab204 100644
--- a/docs/latest/algorithms/template.html
+++ b/docs/latest/algorithms/template.html
@@ -185,7 +185,7 @@ Stub</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/distributed/flink-bindings.html
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diff --git a/docs/latest/distributed/flink-bindings.html 
b/docs/latest/distributed/flink-bindings.html
index 1ccf50e..c3a7a50 100644
--- a/docs/latest/distributed/flink-bindings.html
+++ b/docs/latest/distributed/flink-bindings.html
@@ -218,7 +218,7 @@
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/distributed/h2o-internals.html
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diff --git a/docs/latest/distributed/h2o-internals.html 
b/docs/latest/distributed/h2o-internals.html
index 4d49e32..94aea70 100644
--- a/docs/latest/distributed/h2o-internals.html
+++ b/docs/latest/distributed/h2o-internals.html
@@ -217,7 +217,7 @@
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/distributed/spark-bindings/faq.html
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diff --git a/docs/latest/distributed/spark-bindings/faq.html 
b/docs/latest/distributed/spark-bindings/faq.html
index ff30bce..3632e14 100644
--- a/docs/latest/distributed/spark-bindings/faq.html
+++ b/docs/latest/distributed/spark-bindings/faq.html
@@ -222,7 +222,7 @@ or mis-identified classes.</li>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/distributed/spark-bindings/index.html
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diff --git a/docs/latest/distributed/spark-bindings/index.html 
b/docs/latest/distributed/spark-bindings/index.html
index 2dae645..5a86a34 100644
--- a/docs/latest/distributed/spark-bindings/index.html
+++ b/docs/latest/distributed/spark-bindings/index.html
@@ -273,7 +273,7 @@ Spark, Flink and H20.</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/index.html
----------------------------------------------------------------------
diff --git a/docs/latest/index.html b/docs/latest/index.html
index d78820f..0514d2f 100644
--- a/docs/latest/index.html
+++ b/docs/latest/index.html
@@ -195,7 +195,7 @@ application, and then invoke Mahout’s mathematically 
expressive Scala DSL when
 
 <h2 id="samsara-scala-dsl-syntactic-sugar">Samsara Scala-DSL (Syntactic 
Sugar)</h2>
 
-<p>So when you get to a point in your code where you’re ready to math it up 
(in this example Spark) you can elegently express 
+<p>So when you get to a point in your code where you’re ready to math it up 
(in this example Spark) you can elegantly express 
 yourself mathematically.</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>implicit val sdc: 
org.apache.mahout.sparkbindings.SparkDistributedContext = sc2sdc(sc)
@@ -207,7 +207,7 @@ val C = A.t %*% A + A %*% B.t
 </code></pre>
 </div>
 
-<p>We’ve defined a <code 
class="highlighter-rouge">MahoutDistributedContext</code> (which is a wrapper 
on the Spark Context), and two Disitributed Row Matrices (DRMs)
+<p>We’ve defined a <code 
class="highlighter-rouge">MahoutDistributedContext</code> (which is a wrapper 
on the Spark Context), and two Distributed Row Matrices (DRMs)
 which are wrappers around RDDs (in Spark).</p>
 
 <h2 id="logical--physical-dag">Logical / Physical DAG</h2>
@@ -219,10 +219,10 @@ which are wrappers around RDDs (in Spark).</p>
 </div>
 
 <p>Which is</p>
-<center>$$\mathbf{A^\intercal A}$$</center>
+<center>\(\mathbf{A^\intercal A}\)</center>
 
-<p>Transposing a large matrix is a very expensive thing to do, and in this 
case we don’t actually need to do it. There is a
-more efficient way to calculate <foo>$$\mathbf{A^\intercal A}$$</foo> that 
doesn’t require a physical transpose.</p>
+<p>Transposing a large matrix is a very expensive thing to do, and in this 
case we don’t actually need to do it: there is a
+more efficient way to calculate <foo>\(\mathbf{A^\intercal A}\)</foo> that 
doesn’t require a physical transpose.</p>
 
 <p>(Image showing this)</p>
 
@@ -233,11 +233,11 @@ more efficient way to calculate 
<foo>$$\mathbf{A^\intercal A}$$</foo> that doesn
 </div>
 
 <p>There’s a little more magic that happens at this level, but the punchline 
is <em>Mahout translates the pretty scala into a
-a series of operators, which at the next level are turned implemented at the 
engine</em>.</p>
+a series of operators, which are implemented at engine level</em>.</p>
 
 <h2 id="engine-bindings-and-engine-level-ops">Engine Bindings and Engine Level 
Ops</h2>
 
-<p>When one creates new engine bindings, one is in essence defining</p>
+<p>When one creates new engine bindings, one is in essence defining:</p>
 
 <ol>
   <li>What the engine specific underlying structure for a DRM is (in Spark its 
an RDD).  The underlying structure also has 
@@ -246,28 +246,27 @@ rows of <code 
class="highlighter-rouge">MahoutVector</code>s, so in Spark <code
 implementing things like <code class="highlighter-rouge">AtA</code> on an RDD. 
See <a 
href="https://github.com/apache/mahout/tree/master/spark/src/main/scala/org/apache/mahout/sparkbindings";>the
 sparkbindings on github</a></li>
 </ol>
 
-<p>Now your mathematically expresive Samsara Scala code has been translated 
into optimized engine specific functions.</p>
+<p>Now your mathematically expressive Samsara Scala code has been translated 
into optimized engine specific functions.</p>
 
 <h2 id="native-solvers">Native Solvers</h2>
 
-<p>Recall how I said the rows of the DRMs are <code 
class="highlighter-rouge">org.apache.mahout.math.Vector</code>.  Here is where 
this becomes important. I’m going 
+<p>Recall how I said that rows of the DRMs are <code 
class="highlighter-rouge">org.apache.mahout.math.Vector</code>.  Here is where 
this becomes important. I’m going 
 to explain this in the context of Spark, but the principals apply to all 
distributed backends.</p>
 
 <p>If you are familiar with how mapping and reducing in Spark, then envision 
this RDD of <code class="highlighter-rouge">MahoutVector</code>s,  each 
partition, 
-and indexed collection of vectors is a <em>block</em> of the distributed 
matrix, however this <em>block</em> is totally incore, and therefor
-is treated like an in core matrix.</p>
+and indexed collection of vectors is a <em>block</em> of the distributed 
matrix, however this <em>block</em> is totally in-core, and therefor is treated 
like an in-core matrix.</p>
 
-<p>Now Mahout defines its own incore BLAS packs and refers to them as 
<em>Native Solvers</em>.  The default native solver is just plain
+<p>Now Mahout defines its own in-core BLAS packs and refers to them as 
<em>Native Solvers</em>.  The default native solver is just plain
 old JVM, which is painfully slow, but works just about anywhere.</p>
 
-<p>When the data gets to the node and an operation on the matrix block is 
called.  In the same way Mahout converts abstract
-operators on the DRM that are implemented on various distributed engines, it 
calls abstract operators on the incore matrix 
+<p>When the data gets to the node, an operation on the matrix block is called. 
 In the same way Mahout converts abstract
+operators on the DRM that are implemented on various distributed engines, it 
calls abstract operators on the in-core matrix 
 and vectors which are implemented on various native solvers.</p>
 
-<p>The default “native solver” is the JVM, which isn’t native at all- 
and if no actual native solvers are present operations 
+<p>The default “native solver” is the JVM, which isn’t native at all, 
and if no actual native solvers are present operations 
 will fall back to this. However, IF a native solver is present (the jar was 
added to the notebook), then the magic will happen.</p>
 
-<p>Imagine still we have our Spark executor- it has this block of a matrix 
sitting in its core. Now let’s suppose the <code 
class="highlighter-rouge">ViennaCl-OMP</code>
+<p>Imagine still we have our Spark executor: it has this block of a matrix 
sitting in its core. Now let’s suppose the <code 
class="highlighter-rouge">ViennaCl-OMP</code>
 native solver is in use.  When Spark calls an operation on this incore matrix, 
the matrix dumps out of the JVM and the 
 calculation is carried out on <em>all available CPUs</em>.</p>
 
@@ -276,8 +275,8 @@ calculation is carried out on <em>all available 
CPUs</em>.</p>
 <p>Once the operations are complete, the result is loaded back up into the 
JVM, and Spark (or whatever distributed engine) and 
 shipped back to the driver.</p>
 
-<p>The native solver operatoins are only defined on <code 
class="highlighter-rouge">org.apache.mahout.math.Vector</code> and <code 
class="highlighter-rouge">org.apache.mahout.math.Matrix</code>, which is 
-why it is critical that the underlying structure composed row-wise of <code 
class="highlighter-rouge">Vector</code> or <code 
class="highlighter-rouge">Matrices</code>.</p>
+<p>The native solver operations are only defined on <code 
class="highlighter-rouge">org.apache.mahout.math.Vector</code> and <code 
class="highlighter-rouge">org.apache.mahout.math.Matrix</code>, which is 
+why it is critical that the underlying structure is composed row-wise by <code 
class="highlighter-rouge">Vector</code> or <code 
class="highlighter-rouge">Matrices</code>.</p>
 
 
     </div>
@@ -290,7 +289,7 @@ why it is critical that the underlying structure composed 
row-wise of <code clas
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/mahout-samsara/faq.html
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diff --git a/docs/latest/mahout-samsara/faq.html 
b/docs/latest/mahout-samsara/faq.html
index 1ddfae8..949b81d 100644
--- a/docs/latest/mahout-samsara/faq.html
+++ b/docs/latest/mahout-samsara/faq.html
@@ -222,7 +222,7 @@ or mis-identified classes.</li>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/mahout-samsara/in-core-reference.html
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diff --git a/docs/latest/mahout-samsara/in-core-reference.html 
b/docs/latest/mahout-samsara/in-core-reference.html
index 509ecef..b06de0d 100644
--- a/docs/latest/mahout-samsara/in-core-reference.html
+++ b/docs/latest/mahout-samsara/in-core-reference.html
@@ -414,7 +414,7 @@ a !== b
 </code></pre>
 </div>
 
-<p><em>note: Transposition is currently handled via view, i.e. updating a 
transposed matrix will be updating the original.</em>  Also computing something 
like <code class="highlighter-rouge">$$\mathbf{X^\top}\mathbf{X}$$</code>:</p>
+<p><em>note: Transposition is currently handled via view, i.e. updating a 
transposed matrix will be updating the original.</em>  Also computing something 
like <code class="highlighter-rouge">\(\mathbf{X^\top}\mathbf{X}\)</code>:</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>val XtX = X.t %*% X
 </code></pre>
@@ -470,19 +470,19 @@ a !== b
 
 <p><strong>Solving linear equation systems and matrix inversion:</strong> 
fully similar to R semantics; there are three forms of invocation:</p>
 
-<p>Solve <code class="highlighter-rouge">$$\mathbf{AX}=\mathbf{B}$$</code>:</p>
+<p>Solve <code class="highlighter-rouge">\(\mathbf{AX}=\mathbf{B}\)</code>:</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>solve(A, B)
 </code></pre>
 </div>
 
-<p>Solve <code class="highlighter-rouge">$$\mathbf{Ax}=\mathbf{b}$$</code>:</p>
+<p>Solve <code class="highlighter-rouge">\(\mathbf{Ax}=\mathbf{b}\)</code>:</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>solve(A, b)
 </code></pre>
 </div>
 
-<p>Compute <code class="highlighter-rouge">$$\mathbf{A^{-1}}$$</code>:</p>
+<p>Compute <code class="highlighter-rouge">\(\mathbf{A^{-1}}\)</code>:</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>solve(A)
 </code></pre>
@@ -520,19 +520,19 @@ m.rowMeans
 
 <h4 id="random-matrices">Random Matrices</h4>
 
-<p><code class="highlighter-rouge">$$\mathcal{U}$$</code>(0,1) random matrix 
view:</p>
+<p><code class="highlighter-rouge">\(\mathcal{U}\)</code>(0,1) random matrix 
view:</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>val incCoreA = 
Matrices.uniformView(m, n, seed)
 </code></pre>
 </div>
 
-<p><code class="highlighter-rouge">$$\mathcal{U}$$</code>(-1,1) random matrix 
view:</p>
+<p><code class="highlighter-rouge">\(\mathcal{U}\)</code>(-1,1) random matrix 
view:</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>val incCoreA = 
Matrices.symmetricUniformView(m, n, seed)
 </code></pre>
 </div>
 
-<p><code class="highlighter-rouge">$$\mathcal{N}$$</code>(-1,1) random matrix 
view:</p>
+<p><code class="highlighter-rouge">\(\mathcal{N}\)</code>(-1,1) random matrix 
view:</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>val incCoreA = 
Matrices.gaussianView(m, n, seed)
 </code></pre>
@@ -578,7 +578,7 @@ Similarly **row.all** produces an iterator over all 
elements in a row (Vector).
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
     </div>
 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/mahout-samsara/out-of-core-reference.html
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diff --git a/docs/latest/mahout-samsara/out-of-core-reference.html 
b/docs/latest/mahout-samsara/out-of-core-reference.html
index 1b33383..d77131a 100644
--- a/docs/latest/mahout-samsara/out-of-core-reference.html
+++ b/docs/latest/mahout-samsara/out-of-core-reference.html
@@ -324,7 +324,7 @@ inCoreA /: B
 
 <p><strong>Matrix-matrix multiplication %*%</strong>:</p>
 
-<p><code class="highlighter-rouge">$$\mathbf{M}=\mathbf{AB}$$</code></p>
+<p><code class="highlighter-rouge">\(\mathbf{M}=\mathbf{AB}\)</code></p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>A %*% B
 A %*% inCoreB
@@ -336,7 +336,7 @@ A %*%: B
 <p><em>Note: same as above, whenever operator arguments include both in-core 
and out-of-core arguments, the operator can only be associated with the 
out-of-core (DRM) argument to support the distributed implementation.</em></p>
 
 <p><strong>Matrix-vector multiplication %*%</strong>
-Currently we support a right multiply product of a DRM and an in-core 
Vector(<code class="highlighter-rouge">$$\mathbf{Ax}$$</code>) resulting in a 
single column DRM, which then can be collected in front (usually the desired 
outcome):</p>
+Currently we support a right multiply product of a DRM and an in-core 
Vector(<code class="highlighter-rouge">\(\mathbf{Ax}\)</code>) resulting in a 
single column DRM, which then can be collected in front (usually the desired 
outcome):</p>
 
 <div class="highlighter-rouge"><pre class="highlight"><code>val Ax = A %*% x
 val inCoreX = Ax.collect(::, 0)
@@ -356,7 +356,7 @@ A / 5.0
 </code></pre>
 </div>
 
-<p>Note that <code class="highlighter-rouge">5.0 -: A</code> means <code 
class="highlighter-rouge">$$m_{ij} = 5 - a_{ij}$$</code> and <code 
class="highlighter-rouge">5.0 /: A</code> means <code 
class="highlighter-rouge">$$m_{ij} = \frac{5}{a{ij}}$$</code> for all elements 
of the result.</p>
+<p>Note that <code class="highlighter-rouge">5.0 -: A</code> means <code 
class="highlighter-rouge">\(m_{ij} = 5 - a_{ij}\)</code> and <code 
class="highlighter-rouge">5.0 /: A</code> means <code 
class="highlighter-rouge">\(m_{ij} = \frac{5}{a{ij}}\)</code> for all elements 
of the result.</p>
 
 <h4 id="slicing">Slicing</h4>
 
@@ -551,7 +551,7 @@ val myKeys = drmA.keys
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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@@ -177,7 +177,7 @@
 
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@@ -177,7 +177,7 @@
 
   <footer class="footer bg-light">
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@@ -177,7 +177,7 @@
 
   <footer class="footer bg-light">
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diff --git a/docs/latest/quickstart.html b/docs/latest/quickstart.html
index 167ddce..3720462 100644
--- a/docs/latest/quickstart.html
+++ b/docs/latest/quickstart.html
@@ -231,7 +231,7 @@ If you would like to import the latest release of mahout 
into a java project, ad
 
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-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ b/docs/latest/tutorials/cco-lastfm/index.html
@@ -329,7 +329,7 @@ Finally let’s sort that vector out and get some user ids 
and strengths.</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ b/docs/latest/tutorials/eigenfaces/index.html
@@ -302,7 +302,7 @@ tar -xzf lfw-deepfunneled.tgz
 
   <footer class="footer bg-light">
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-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ b/docs/latest/tutorials/intro-cooccurrence-spark/index.html
@@ -653,7 +653,7 @@ on the popularity field. If we use the ecom example but use 
the query to get “
 
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-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+++ b/docs/latest/tutorials/map-reduce/classification/bankmarketing-example.html
@@ -224,7 +224,7 @@ to encode the features in the dataset into a vector. 
Afterwards the model is tes
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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--- a/docs/latest/tutorials/map-reduce/classification/breiman-example.html
+++ b/docs/latest/tutorials/map-reduce/classification/breiman-example.html
@@ -243,7 +243,7 @@ iterations</li>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ b/docs/latest/tutorials/map-reduce/classification/twenty-newsgroups.html
@@ -387,7 +387,7 @@ Reliability (standard deviation)            0.2131
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ 
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@@ -230,7 +230,7 @@ directory:  country.txt, country10.txt and country2.txt.  
You can edit these cat
 
   <footer class="footer bg-light">
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-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ b/docs/latest/tutorials/map-reduce/clustering/20newsgroups.html
@@ -180,7 +180,7 @@
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ b/docs/latest/tutorials/map-reduce/clustering/canopy-commandline.html
@@ -248,7 +248,7 @@ to view all outputs.</li>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ 
b/docs/latest/tutorials/map-reduce/clustering/clustering-of-synthetic-control-data.html
@@ -238,7 +238,7 @@
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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+++ 
b/docs/latest/tutorials/map-reduce/clustering/clustering-seinfeld-episodes.html
@@ -180,7 +180,7 @@ Mahout.</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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--- a/docs/latest/tutorials/map-reduce/clustering/clusteringyourdata.html
+++ b/docs/latest/tutorials/map-reduce/clustering/clusteringyourdata.html
@@ -304,7 +304,7 @@ good at seeing (making up) patterns.
 
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@@ -274,7 +274,7 @@ to view all outputs.</li>
 
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@@ -270,7 +270,7 @@ to view all outputs.</li>
 
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-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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@@ -260,7 +260,7 @@ to view all outputs.</li>
 
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-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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@@ -189,7 +189,7 @@ algorithms.</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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@@ -216,7 +216,7 @@ demonstrate the various ways one might inspect the outcome 
of various jobs.
 
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@@ -222,7 +222,7 @@ iterations.</p>
 
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@@ -189,7 +189,7 @@ database (structured).</p>
 
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@@ -357,7 +357,7 @@ parameters?
 
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--- a/docs/latest/tutorials/map-reduce/misc/perceptron-and-winnow.html
+++ b/docs/latest/tutorials/map-reduce/misc/perceptron-and-winnow.html
@@ -211,7 +211,7 @@ parallelisation will be added.</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/misc/testing.html
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diff --git a/docs/latest/tutorials/map-reduce/misc/testing.html 
b/docs/latest/tutorials/map-reduce/misc/testing.html
index a9d0b11..e77a460 100644
--- a/docs/latest/tutorials/map-reduce/misc/testing.html
+++ b/docs/latest/tutorials/map-reduce/misc/testing.html
@@ -220,7 +220,7 @@ of a great many utilities and algorithms. A much smaller 
percent include
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/misc/using-mahout-with-python-via-jpype.html
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diff --git 
a/docs/latest/tutorials/map-reduce/misc/using-mahout-with-python-via-jpype.html 
b/docs/latest/tutorials/map-reduce/misc/using-mahout-with-python-via-jpype.html
index 20eeb52..98d51cf 100644
--- 
a/docs/latest/tutorials/map-reduce/misc/using-mahout-with-python-via-jpype.html
+++ 
b/docs/latest/tutorials/map-reduce/misc/using-mahout-with-python-via-jpype.html
@@ -389,7 +389,7 @@ found by mahout,</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/intro-als-hadoop.html
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diff --git a/docs/latest/tutorials/map-reduce/recommender/intro-als-hadoop.html 
b/docs/latest/tutorials/map-reduce/recommender/intro-als-hadoop.html
index 1de90c1..925fb53 100644
--- a/docs/latest/tutorials/map-reduce/recommender/intro-als-hadoop.html
+++ b/docs/latest/tutorials/map-reduce/recommender/intro-als-hadoop.html
@@ -273,7 +273,7 @@ Remember to translate the Mahout ids back into your 
application specific ids.</p
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/intro-cooccurrence-spark.html
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a/docs/latest/tutorials/map-reduce/recommender/intro-cooccurrence-spark.html 
b/docs/latest/tutorials/map-reduce/recommender/intro-cooccurrence-spark.html
index a4be069..12b1d7f 100644
--- a/docs/latest/tutorials/map-reduce/recommender/intro-cooccurrence-spark.html
+++ b/docs/latest/tutorials/map-reduce/recommender/intro-cooccurrence-spark.html
@@ -644,7 +644,7 @@ on the popularity field. If we use the ecom example but use 
the query to get “
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/intro-itembased-hadoop.html
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diff --git 
a/docs/latest/tutorials/map-reduce/recommender/intro-itembased-hadoop.html 
b/docs/latest/tutorials/map-reduce/recommender/intro-itembased-hadoop.html
index abecaa4..3a179cd 100644
--- a/docs/latest/tutorials/map-reduce/recommender/intro-itembased-hadoop.html
+++ b/docs/latest/tutorials/map-reduce/recommender/intro-itembased-hadoop.html
@@ -230,7 +230,7 @@
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/matrix-factorization.html
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diff --git 
a/docs/latest/tutorials/map-reduce/recommender/matrix-factorization.html 
b/docs/latest/tutorials/map-reduce/recommender/matrix-factorization.html
index 3318b58..ae34089 100644
--- a/docs/latest/tutorials/map-reduce/recommender/matrix-factorization.html
+++ b/docs/latest/tutorials/map-reduce/recommender/matrix-factorization.html
@@ -390,7 +390,7 @@ Mahout also offers a <a 
href="https://mahout.apache.org/users/recommender/intro-
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/quickstart.html
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diff --git a/docs/latest/tutorials/map-reduce/recommender/quickstart.html 
b/docs/latest/tutorials/map-reduce/recommender/quickstart.html
index 6e3d17a..e41157b 100644
--- a/docs/latest/tutorials/map-reduce/recommender/quickstart.html
+++ b/docs/latest/tutorials/map-reduce/recommender/quickstart.html
@@ -203,7 +203,7 @@ and  <a 
href="http://occamsmachete.com/ml/2014/09/09/mahout-on-spark-whats-new-i
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/recommender-documentation.html
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diff --git 
a/docs/latest/tutorials/map-reduce/recommender/recommender-documentation.html 
b/docs/latest/tutorials/map-reduce/recommender/recommender-documentation.html
index a8db1c8..937700d 100644
--- 
a/docs/latest/tutorials/map-reduce/recommender/recommender-documentation.html
+++ 
b/docs/latest/tutorials/map-reduce/recommender/recommender-documentation.html
@@ -451,7 +451,7 @@ Research and Development in Information Retrieval (SIGIR 
99), pp. 230-237,
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
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 </footer>
 

http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/recommender-first-timer-faq.html
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index 8292d69..a537a96 100644
--- 
a/docs/latest/tutorials/map-reduce/recommender/recommender-first-timer-faq.html
+++ 
b/docs/latest/tutorials/map-reduce/recommender/recommender-first-timer-faq.html
@@ -223,7 +223,7 @@ only periodically – perhaps on the order of minutes.</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/map-reduce/recommender/userbased-5-minutes.html
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diff --git 
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--- a/docs/latest/tutorials/map-reduce/recommender/userbased-5-minutes.html
+++ b/docs/latest/tutorials/map-reduce/recommender/userbased-5-minutes.html
@@ -301,7 +301,7 @@ Note: if you run this test multiple times, you will get 
different results, becau
 
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     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/misc/contributing-algos/index.html
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b/docs/latest/tutorials/misc/contributing-algos/index.html
index 7c3e0b5..14e35bb 100644
--- a/docs/latest/tutorials/misc/contributing-algos/index.html
+++ b/docs/latest/tutorials/misc/contributing-algos/index.html
@@ -635,7 +635,7 @@ assigned, then a descriptive title.</p>
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
under the Apache License, Version 2.0.
+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/misc/how-to-build-an-app.html
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diff --git a/docs/latest/tutorials/misc/how-to-build-an-app.html 
b/docs/latest/tutorials/misc/how-to-build-an-app.html
index 7fa21c9..2ed50b1 100644
--- a/docs/latest/tutorials/misc/how-to-build-an-app.html
+++ b/docs/latest/tutorials/misc/how-to-build-an-app.html
@@ -455,7 +455,7 @@ category indicator matrix:
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/misc/mahout-in-zeppelin/index.html
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index 66eaffb..56fe375 100644
--- a/docs/latest/tutorials/misc/mahout-in-zeppelin/index.html
+++ b/docs/latest/tutorials/misc/mahout-in-zeppelin/index.html
@@ -453,7 +453,7 @@ scatterplot3d(data, color="green")
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/samsara/classify-a-doc-from-the-shell.html
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diff --git a/docs/latest/tutorials/samsara/classify-a-doc-from-the-shell.html 
b/docs/latest/tutorials/samsara/classify-a-doc-from-the-shell.html
index b4a2151..01ddb03 100644
--- a/docs/latest/tutorials/samsara/classify-a-doc-from-the-shell.html
+++ b/docs/latest/tutorials/samsara/classify-a-doc-from-the-shell.html
@@ -463,7 +463,7 @@ classifyText("Hello world from London")
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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http://git-wip-us.apache.org/repos/asf/mahout/blob/9b7db9c6/docs/latest/tutorials/samsara/play-with-shell.html
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diff --git a/docs/latest/tutorials/samsara/play-with-shell.html 
b/docs/latest/tutorials/samsara/play-with-shell.html
index fbe89ff..8a855b0 100644
--- a/docs/latest/tutorials/samsara/play-with-shell.html
+++ b/docs/latest/tutorials/samsara/play-with-shell.html
@@ -314,15 +314,15 @@ val drmData = drmParallelize(dense(
 <p>Have a look at this matrix. The first four columns represent the 
ingredients 
 (our features) and the last column (the rating) is the target variable for 
 our regression. <a 
href="https://en.wikipedia.org/wiki/Linear_regression";>Linear regression</a> 
-assumes that the <strong>target variable</strong> <code 
class="highlighter-rouge">$$\mathbf{y}$$</code> is generated by the
-linear combination of <strong>the feature matrix</strong> <code 
class="highlighter-rouge">$$\mathbf{X}$$</code> with the
-<strong>parameter vector</strong> <code 
class="highlighter-rouge">$$\boldsymbol{\beta}$$</code> plus the
- <strong>noise</strong> <code 
class="highlighter-rouge">$$\boldsymbol{\varepsilon}$$</code>, summarized in 
the formula
-<code 
class="highlighter-rouge">$$\mathbf{y}=\mathbf{X}\boldsymbol{\beta}+\boldsymbol{\varepsilon}$$</code>.
+assumes that the <strong>target variable</strong> <code 
class="highlighter-rouge">\(\mathbf{y}\)</code> is generated by the 
+linear combination of <strong>the feature matrix</strong> <code 
class="highlighter-rouge">\(\mathbf{X}\)</code> with the 
+<strong>parameter vector</strong> <code 
class="highlighter-rouge">\(\boldsymbol{\beta}\)</code> plus the
+ <strong>noise</strong> <code 
class="highlighter-rouge">\(\boldsymbol{\varepsilon}\)</code>, summarized in 
the formula 
+<code 
class="highlighter-rouge">\(\mathbf{y}=\mathbf{X}\boldsymbol{\beta}+\boldsymbol{\varepsilon}\)</code>.
 
 Our goal is to find an estimate of the parameter vector 
-<code class="highlighter-rouge">$$\boldsymbol{\beta}$$</code> that explains 
the data very well.</p>
+<code class="highlighter-rouge">\(\boldsymbol{\beta}\)</code> that explains 
the data very well.</p>
 
-<p>As a first step, we extract <code 
class="highlighter-rouge">$$\mathbf{X}$$</code> and <code 
class="highlighter-rouge">$$\mathbf{y}$$</code> from our data matrix. We get 
<em>X</em> by slicing: we take all rows (denoted by <code 
class="highlighter-rouge">::</code>) and the first four columns, which have the 
ingredients in milligrams as content. Note that the result is again a DRM. The 
shell will not execute this code yet, it saves the history of operations and 
defers the execution until we really access a result. <strong>Mahout’s DSL 
automatically optimizes and parallelizes all operations on DRMs and runs them 
on Apache Spark.</strong></p>
+<p>As a first step, we extract <code 
class="highlighter-rouge">\(\mathbf{X}\)</code> and <code 
class="highlighter-rouge">\(\mathbf{y}\)</code> from our data matrix. We get 
<em>X</em> by slicing: we take all rows (denoted by <code 
class="highlighter-rouge">::</code>) and the first four columns, which have the 
ingredients in milligrams as content. Note that the result is again a DRM. The 
shell will not execute this code yet, it saves the history of operations and 
defers the execution until we really access a result. <strong>Mahout’s DSL 
automatically optimizes and parallelizes all operations on DRMs and runs them 
on Apache Spark.</strong></p>
 
 <div class="codehilite"><pre>
 val drmX = drmData(::, 0 until 4)
@@ -334,27 +334,27 @@ val drmX = drmData(::, 0 until 4)
 val y = drmData.collect(::, 4)
 </pre></div>
 
-<p>Now we are ready to think about a mathematical way to estimate the 
parameter vector <em>β</em>. A simple textbook approach is <a 
href="https://en.wikipedia.org/wiki/Ordinary_least_squares";>ordinary least 
squares (OLS)</a>, which minimizes the sum of residual squares between the true 
target variable and the prediction of the target variable. In OLS, there is 
even a closed form expression for estimating <code 
class="highlighter-rouge">$$\boldsymbol{\beta}$$</code> as
-<code 
class="highlighter-rouge">$$\left(\mathbf{X}^{\top}\mathbf{X}\right)^{-1}\mathbf{X}^{\top}\mathbf{y}$$</code>.</p>
+<p>Now we are ready to think about a mathematical way to estimate the 
parameter vector <em>β</em>. A simple textbook approach is <a 
href="https://en.wikipedia.org/wiki/Ordinary_least_squares";>ordinary least 
squares (OLS)</a>, which minimizes the sum of residual squares between the true 
target variable and the prediction of the target variable. In OLS, there is 
even a closed form expression for estimating <code 
class="highlighter-rouge">\(\boldsymbol{\beta}\)</code> as 
+<code 
class="highlighter-rouge">\(\left(\mathbf{X}^{\top}\mathbf{X}\right)^{-1}\mathbf{X}^{\top}\mathbf{y}\)</code>.</p>
 
-<p>The first thing which we compute for this is  <code 
class="highlighter-rouge">$$\mathbf{X}^{\top}\mathbf{X}$$</code>. The code for 
doing this in Mahout’s scala DSL maps directly to the mathematical formula. 
The operation <code class="highlighter-rouge">.t()</code> transposes a matrix 
and analogous to R <code class="highlighter-rouge">%*%</code> denotes matrix 
multiplication.</p>
+<p>The first thing which we compute for this is  <code 
class="highlighter-rouge">\(\mathbf{X}^{\top}\mathbf{X}\)</code>. The code for 
doing this in Mahout’s scala DSL maps directly to the mathematical formula. 
The operation <code class="highlighter-rouge">.t()</code> transposes a matrix 
and analogous to R <code class="highlighter-rouge">%*%</code> denotes matrix 
multiplication.</p>
 
 <div class="codehilite"><pre>
 val drmXtX = drmX.t %*% drmX
 </pre></div>
 
-<p>The same is true for computing <code 
class="highlighter-rouge">$$\mathbf{X}^{\top}\mathbf{y}$$</code>. We can simply 
type the math in scala expressions into the shell. Here, <em>X</em> lives in 
the cluster, while is <em>y</em> in the memory of the driver, and the result is 
a DRM again.</p>
+<p>The same is true for computing <code 
class="highlighter-rouge">\(\mathbf{X}^{\top}\mathbf{y}\)</code>. We can simply 
type the math in scala expressions into the shell. Here, <em>X</em> lives in 
the cluster, while is <em>y</em> in the memory of the driver, and the result is 
a DRM again.</p>
 <div class="codehilite"><pre>
 val drmXty = drmX.t %*% y
 </pre></div>
 
-<p>We’re nearly done. The next step we take is to fetch <code 
class="highlighter-rouge">$$\mathbf{X}^{\top}\mathbf{X}$$</code> and
-<code class="highlighter-rouge">$$\mathbf{X}^{\top}\mathbf{y}$$</code> into 
the memory of our driver machine (we are targeting
+<p>We’re nearly done. The next step we take is to fetch <code 
class="highlighter-rouge">\(\mathbf{X}^{\top}\mathbf{X}\)</code> and 
+<code class="highlighter-rouge">\(\mathbf{X}^{\top}\mathbf{y}\)</code> into 
the memory of our driver machine (we are targeting 
 features matrices that are tall and skinny , 
-so we can assume that <code 
class="highlighter-rouge">$$\mathbf{X}^{\top}\mathbf{X}$$</code> is small enough
+so we can assume that <code 
class="highlighter-rouge">\(\mathbf{X}^{\top}\mathbf{X}\)</code> is small 
enough 
 to fit in). Then, we provide them to an in-memory solver (Mahout provides 
 the an analog to R’s <code class="highlighter-rouge">solve()</code> for 
that) which computes <code class="highlighter-rouge">beta</code>, our 
-OLS estimate of the parameter vector <code 
class="highlighter-rouge">$$\boldsymbol{\beta}$$</code>.</p>
+OLS estimate of the parameter vector <code 
class="highlighter-rouge">\(\boldsymbol{\beta}\)</code>.</p>
 
 <div class="codehilite"><pre>
 val XtX = drmXtX.collect
@@ -371,9 +371,9 @@ as much as possible, while still retaining decent 
performance and
 scalability.</p>
 
 <p>We can now check how well our model fits its training data. 
-First, we multiply the feature matrix <code 
class="highlighter-rouge">$$\mathbf{X}$$</code> by our estimate of
-<code class="highlighter-rouge">$$\boldsymbol{\beta}$$</code>. Then, we look 
at the difference (via L2-norm) of
-the target variable <code class="highlighter-rouge">$$\mathbf{y}$$</code> to 
the fitted target variable:</p>
+First, we multiply the feature matrix <code 
class="highlighter-rouge">\(\mathbf{X}\)</code> by our estimate of 
+<code class="highlighter-rouge">\(\boldsymbol{\beta}\)</code>. Then, we look 
at the difference (via L2-norm) of 
+the target variable <code class="highlighter-rouge">\(\mathbf{y}\)</code> to 
the fitted target variable:</p>
 
 <div class="codehilite"><pre>
 val yFitted = (drmX %*% beta).collect(::, 0)
@@ -406,7 +406,7 @@ def goodnessOfFit(drmX: DrmLike[Int], beta: Vector, y: 
Vector) = {
 model. Usually there is a constant bias term added to the model. Without 
 that, our model always crosses through the origin and we only learn the 
 right angle. An easy way to add such a bias term to our model is to add a 
-column of ones to the feature matrix <code 
class="highlighter-rouge">$$\mathbf{X}$$</code>.
+column of ones to the feature matrix <code 
class="highlighter-rouge">\(\mathbf{X}\)</code>. 
 The corresponding weight in the parameter vector will then be the bias 
term.</p>
 
 <p>Here is how we add a bias column:</p>
@@ -447,7 +447,7 @@ goodness
 
   <footer class="footer bg-light">
     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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index 7c3e4e1..8f6934c 100644
--- a/docs/latest/tutorials/samsara/playing-with-samsara-flink-batch.html
+++ b/docs/latest/tutorials/samsara/playing-with-samsara-flink-batch.html
@@ -293,7 +293,7 @@ object ReadCsvExample {
 
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     <div class="container text-center small">
-        Copyright &copy; 2014-2017 The Apache Software Foundation, Licensed 
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+        Copyright &copy; 2014-2018 The Apache Software Foundation, Licensed 
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index b0b4819..a89268b 100644
--- a/docs/latest/tutorials/samsara/spark-naive-bayes.html
+++ b/docs/latest/tutorials/samsara/spark-naive-bayes.html
@@ -181,38 +181,38 @@
 <p>As described in <a 
href="http://people.csail.mit.edu/jrennie/papers/icml03-nb.pdf";>[1]</a> Mahout 
Naive Bayes is broken down into the following steps (assignments are over all 
possible index values):</p>
 
 <ul>
-  <li>Let <code 
class="highlighter-rouge">$$\vec{d}=(\vec{d_1},...,\vec{d_n})$$</code> be a set 
of documents; <code class="highlighter-rouge">$$d_{ij}$$</code> is the count of 
word <code class="highlighter-rouge">$$i$$</code> in document <code 
class="highlighter-rouge">$$j$$</code>.</li>
-  <li>Let <code class="highlighter-rouge">$$\vec{y}=(y_1,...,y_n)$$</code> be 
their labels.</li>
-  <li>Let <code class="highlighter-rouge">$$\alpha_i$$</code> be a smoothing 
parameter for all words in the vocabulary; let <code 
class="highlighter-rouge">$$\alpha=\sum_i{\alpha_i}$$</code>.</li>
-  <li><strong>Preprocessing</strong>(via seq2Sparse) TF-IDF transformation and 
L2 length normalization of <code class="highlighter-rouge">$$\vec{d}$$</code>
+  <li>Let <code 
class="highlighter-rouge">\(\vec{d}=(\vec{d_1},...,\vec{d_n})\)</code> be a set 
of documents; <code class="highlighter-rouge">\(d_{ij}\)</code> is the count of 
word <code class="highlighter-rouge">\(i\)</code> in document <code 
class="highlighter-rouge">\(j\)</code>.</li>
+  <li>Let <code class="highlighter-rouge">\(\vec{y}=(y_1,...,y_n)\)</code> be 
their labels.</li>
+  <li>Let <code class="highlighter-rouge">\(\alpha_i\)</code> be a smoothing 
parameter for all words in the vocabulary; let <code 
class="highlighter-rouge">\(\alpha=\sum_i{\alpha_i}\)</code>.</li>
+  <li><strong>Preprocessing</strong>(via seq2Sparse) TF-IDF transformation and 
L2 length normalization of <code class="highlighter-rouge">\(\vec{d}\)</code>
     <ol>
-      <li><code class="highlighter-rouge">$$d_{ij} = 
\sqrt{d_{ij}}$$</code></li>
-      <li><code class="highlighter-rouge">$$d_{ij} = 
d_{ij}\left(\log{\frac{\sum_k1}{\sum_k\delta_{ik}+1}}+1\right)$$</code></li>
-      <li><code class="highlighter-rouge">$$d_{ij} 
=\frac{d_{ij}}{\sqrt{\sum_k{d_{kj}^2}}}$$</code></li>
+      <li><code class="highlighter-rouge">\(d_{ij} = 
\sqrt{d_{ij}}\)</code></li>
+      <li><code class="highlighter-rouge">\(d_{ij} = 
d_{ij}\left(\log{\frac{\sum_k1}{\sum_k\delta_{ik}+1}}+1\right)\)</code></li>
+      <li><code class="highlighter-rouge">\(d_{ij} 
=\frac{d_{ij}}{\sqrt{\sum_k{d_{kj}^2}}}\)</code></li>
     </ol>
   </li>
-  <li><strong>Training: Bayes</strong><code 
class="highlighter-rouge">$$(\vec{d},\vec{y})$$</code> calculate term weights 
<code class="highlighter-rouge">$$w_{ci}$$</code> as:
+  <li><strong>Training: Bayes</strong><code 
class="highlighter-rouge">\((\vec{d},\vec{y})\)</code> calculate term weights 
<code class="highlighter-rouge">\(w_{ci}\)</code> as:
     <ol>
-      <li><code 
class="highlighter-rouge">$$\hat\theta_{ci}=\frac{d_{ic}+\alpha_i}{\sum_k{d_{kc}}+\alpha}$$</code></li>
-      <li><code 
class="highlighter-rouge">$$w_{ci}=\log{\hat\theta_{ci}}$$</code></li>
+      <li><code 
class="highlighter-rouge">\(\hat\theta_{ci}=\frac{d_{ic}+\alpha_i}{\sum_k{d_{kc}}+\alpha}\)</code></li>
+      <li><code 
class="highlighter-rouge">\(w_{ci}=\log{\hat\theta_{ci}}\)</code></li>
     </ol>
   </li>
-  <li><strong>Training: CBayes</strong><code 
class="highlighter-rouge">$$(\vec{d},\vec{y})$$</code> calculate term weights 
<code class="highlighter-rouge">$$w_{ci}$$</code> as:
+  <li><strong>Training: CBayes</strong><code 
class="highlighter-rouge">\((\vec{d},\vec{y})\)</code> calculate term weights 
<code class="highlighter-rouge">\(w_{ci}\)</code> as:
     <ol>
-      <li><code class="highlighter-rouge">$$\hat\theta_{ci} = 
\frac{\sum_{j:y_j\neq c}d_{ij}+\alpha_i}{\sum_{j:y_j\neq 
c}{\sum_k{d_{kj}}}+\alpha}$$</code></li>
-      <li><code 
class="highlighter-rouge">$$w_{ci}=-\log{\hat\theta_{ci}}$$</code></li>
-      <li><code class="highlighter-rouge">$$w_{ci}=\frac{w_{ci}}{\sum_i \lvert 
w_{ci}\rvert}$$</code></li>
+      <li><code class="highlighter-rouge">\(\hat\theta_{ci} = 
\frac{\sum_{j:y_j\neq c}d_{ij}+\alpha_i}{\sum_{j:y_j\neq 
c}{\sum_k{d_{kj}}}+\alpha}\)</code></li>
+      <li><code 
class="highlighter-rouge">\(w_{ci}=-\log{\hat\theta_{ci}}\)</code></li>
+      <li><code class="highlighter-rouge">\(w_{ci}=\frac{w_{ci}}{\sum_i \lvert 
w_{ci}\rvert}\)</code></li>
     </ol>
   </li>
   <li><strong>Label Assignment/Testing:</strong>
     <ol>
-      <li>Let <code class="highlighter-rouge">$$\vec{t}= 
(t_1,...,t_n)$$</code> be a test document; let <code 
class="highlighter-rouge">$$t_i$$</code> be the count of the word <code 
class="highlighter-rouge">$$t$$</code>.</li>
-      <li>Label the document according to <code 
class="highlighter-rouge">$$l(t)=\arg\max_c \sum\limits_{i} t_i 
w_{ci}$$</code></li>
+      <li>Let <code class="highlighter-rouge">\(\vec{t}= 
(t_1,...,t_n)\)</code> be a test document; let <code 
class="highlighter-rouge">\(t_i\)</code> be the count of the word <code 
class="highlighter-rouge">\(t\)</code>.</li>
+      <li>Label the document according to <code 
class="highlighter-rouge">\(l(t)=\arg\max_c \sum\limits_{i} t_i 
w_{ci}\)</code></li>
     </ol>
   </li>
 </ul>
 
-<p>As we can see, the main difference between Bayes and CBayes is the weight 
calculation step.  Where Bayes weighs terms more heavily based on the 
likelihood that they belong to class <code 
class="highlighter-rouge">$$c$$</code>, CBayes seeks to maximize term weights 
on the likelihood that they do not belong to any other class.</p>
+<p>As we can see, the main difference between Bayes and CBayes is the weight 
calculation step.  Where Bayes weighs terms more heavily based on the 
likelihood that they belong to class <code 
class="highlighter-rouge">\(c\)</code>, CBayes seeks to maximize term weights 
on the likelihood that they do not belong to any other class.</p>
 
 <h2 id="running-from-the-command-line">Running from the command line</h2>
 
@@ -334,7 +334,7 @@ Classification and testing on a holdout set can then be 
performed via <code clas
 
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index 39e04cc..7df450d 100644
--- a/feed.xml
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@@ -1,4 +1,4 @@
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xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/"; 
version="3.5.0">Jekyll</generator><link 
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rel="alternate" type="text/html" title="New Website" 
/><published>2017-12-20T22:16:01+00:00</published><updated>2017-12-20T22:16:01+00:00</updated><id>http://mahout.apache.org//news/2017/12/20/new-website</id><content
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index 49651ba..c2c4528 100644
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@@ -269,7 +269,7 @@ given.</p>
 
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index f533398..7d57a17 100644
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@@ -257,7 +257,7 @@ the <a 
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   <footer class="footer bg-light">
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index 1aaef30..ebee4aa 100644
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index ee41ff9..505bd4c 100644
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index a2f95bc..16bc86e 100644
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@@ -292,7 +292,7 @@ measured in seconds, not milliseconds.</p>
 
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