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Posted to commits@mahout.apache.org by ap...@apache.org on 2015/03/20 16:06:11 UTC
svn commit: r1668040 - in /mahout/site/mahout_cms/trunk:
content/users/basics/algorithms.mdtext
content/users/classification/twenty-newsgroups.mdtext templates/standard.html
Author: apalumbo
Date: Fri Mar 20 15:06:11 2015
New Revision: 1668040
URL: http://svn.apache.org/r1668040
Log:
Moved clustering, classification and recommender dirs back to users to not break external links
Modified:
mahout/site/mahout_cms/trunk/content/users/basics/algorithms.mdtext
mahout/site/mahout_cms/trunk/content/users/classification/twenty-newsgroups.mdtext
mahout/site/mahout_cms/trunk/templates/standard.html
Modified: mahout/site/mahout_cms/trunk/content/users/basics/algorithms.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/mahout_cms/trunk/content/users/basics/algorithms.mdtext?rev=1668040&r1=1668039&r2=1668040&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/users/basics/algorithms.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/users/basics/algorithms.mdtext Fri Mar 20 15:06:11 2015
@@ -15,24 +15,24 @@ Title: Algorithms
||
**Collaborative Filtering** *with CLI Drivers*|
User-Based Collaborative Filtering | x | |[x](https://mahout.apache.org/users/algorithms/intro-cooccurrence-spark.html)
- Item-Based Collaborative Filtering | x | [x](https://mahout.apache.org/users/mapreduce/recommender/intro-itembased-hadoop.html) | [x](https://mahout.apache.org/users/algorithms/intro-cooccurrence-spark.html) |
- Matrix Factorization with ALS | x | [x](https://mahout.apache.org/users/mapreduce/recommender/intro-als-hadoop.html) | |
- Matrix Factorization with ALS on Implicit Feedback | x | [x](https://mahout.apache.org/users/mapreduce/recommender/intro-als-hadoop.html) | |
+ Item-Based Collaborative Filtering | x | [x](https://mahout.apache.org/users/recommender/intro-itembased-hadoop.html) | [x](https://mahout.apache.org/users/algorithms/intro-cooccurrence-spark.html) |
+ Matrix Factorization with ALS | x | [x](https://mahout.apache.org/users/recommender/intro-als-hadoop.html) | |
+ Matrix Factorization with ALS on Implicit Feedback | x | [x](https://mahout.apache.org/users/recommender/intro-als-hadoop.html) | |
Weighted Matrix Factorization, SVD++ | x | |
||
**Classification** *with CLI Drivers*| | |
- Logistic Regression - trained via SGD | [x](http://mahout.apache.org/users/mapreduce/classification/logistic-regression.html) |
- Naive Bayes / Complementary Naive Bayes | | [x](https://mahout.apache.org/users/mapreduce/classification/bayesian.html) | [x](https://mahout.apache.org/users/algorithms/spark-naive-bayes.html) |
- Random Forest | | [x](https://mahout.apache.org/users/mapreduce/classification/partial-implementation.html)|
- Hidden Markov Models | [x](https://mahout.apache.org/users/mapreduce/classification/hidden-markov-models.html) |
+ Logistic Regression - trained via SGD | [x](http://mahout.apache.org/users/classification/logistic-regression.html) |
+ Naive Bayes / Complementary Naive Bayes | | [x](https://mahout.apache.org/users/classification/bayesian.html) | [x](https://mahout.apache.org/users/algorithms/spark-naive-bayes.html) |
+ Random Forest | | [x](https://mahout.apache.org/users/classification/partial-implementation.html)|
+ Hidden Markov Models | [x](https://mahout.apache.org/users/classification/hidden-markov-models.html) |
Multilayer Perceptron | x |
||
**Clustering** *with CLI Drivers*||
- Canopy Clustering | [*deprecated*](https://mahout.apache.org/users/mapreduce/clustering/canopy-clustering.html) | [*deprecated*](https://mahout.apache.org/users/mapreduce/clustering/canopy-clustering.html)|
- k-Means Clustering | [x](https://mahout.apache.org/users/mapreduce/clustering/k-means-clustering.html) | [x](https://mahout.apache.org/users/mapreduce/clustering/k-means-clustering.html) |
- Fuzzy k-Means | [x](https://mahout.apache.org/users/mapreduce/clustering/fuzzy-k-means.html) | [x](https://mahout.apache.org/users/mapreduce/clustering/fuzzy-k-means.html)|
- Streaming k-Means | [x](https://mahout.apache.org/users/mapreduce/clustering/streaming-k-means.html) | [x](https://mahout.apache.org/users/mapreduce/clustering/streaming-k-means.html) |
- Spectral Clustering | | [x](https://mahout.apache.org/users/mapreduce/clustering/spectral-clustering.html) |
+ Canopy Clustering | [*deprecated*](https://mahout.apache.org/users/clustering/canopy-clustering.html) | [*deprecated*](https://mahout.apache.org/users/clustering/canopy-clustering.html)|
+ k-Means Clustering | [x](https://mahout.apache.org/users/clustering/k-means-clustering.html) | [x](https://mahout.apache.org/users/clustering/k-means-clustering.html) |
+ Fuzzy k-Means | [x](https://mahout.apache.org/users/clustering/fuzzy-k-means.html) | [x](https://mahout.apache.org/users/clustering/fuzzy-k-means.html)|
+ Streaming k-Means | [x](https://mahout.apache.org/users/clustering/streaming-k-means.html) | [x](https://mahout.apache.org/users/clustering/streaming-k-means.html) |
+ Spectral Clustering | | [x](https://mahout.apache.org/users/clustering/spectral-clustering.html) |
||
**Dimensionality Reduction** *with CLI Drivers - note: most scala-based dimensionality reduction algorithms are available through the [Mahout Math-Scala Core Library for all engines](https://mahout.apache.org/users/sparkbindings/home.html)*||
Singular Value Decomposition | x | x | |
Modified: mahout/site/mahout_cms/trunk/content/users/classification/twenty-newsgroups.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/mahout_cms/trunk/content/users/classification/twenty-newsgroups.mdtext?rev=1668040&r1=1668039&r2=1668040&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/users/classification/twenty-newsgroups.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/users/classification/twenty-newsgroups.mdtext Fri Mar 20 15:06:11 2015
@@ -10,7 +10,7 @@ The 20 newsgroups dataset is a collectio
newsgroup documents, partitioned (nearly) evenly across 20 different
newsgroups. The 20 newsgroups collection has become a popular data set for
experiments in text applications of machine learning techniques, such as
-text classification and text clustering. We will use the [Mahout CBayes](http://mahout.apache.org/users/classification/bayesian.html)
+text classification and text clustering. We will use the [Mahout CBayes](http://mahout.apache.org/users/mapreduce/classification/bayesian.html)
classifier to create a model that would classify a new document into one of
the 20 newsgroups.
Modified: mahout/site/mahout_cms/trunk/templates/standard.html
URL: http://svn.apache.org/viewvc/mahout/site/mahout_cms/trunk/templates/standard.html?rev=1668040&r1=1668039&r2=1668040&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/templates/standard.html (original)
+++ mahout/site/mahout_cms/trunk/templates/standard.html Fri Mar 20 15:06:11 2015
@@ -176,36 +176,36 @@
<li class="dropdown"> <a href="#" class="dropdown-toggle" data-toggle="dropdown">Mahout MapReduce<b class="caret"></b></a>
<ul class="dropdown-menu">
<li class="nav-header">Classification</li>
- <li><a href="/users/mapreduce/classification/bayesian.html">Naive Bayes</a></li>
- <li><a href="/users/mapreduce/classification/hidden-markov-models.html">Hidden Markov Models</a></li>
- <li><a href="/users/mapreduce/classification/logistic-regression.html">Logistic Regression</a></li>
- <li><a href="/users/mapreduce/classification/partial-implementation.html">Random Forest</a></li>
+ <li><a href="/users/classification/bayesian.html">Naive Bayes</a></li>
+ <li><a href="/users/classification/hidden-markov-models.html">Hidden Markov Models</a></li>
+ <li><a href="/users/classification/logistic-regression.html">Logistic Regression</a></li>
+ <li><a href="/users/classification/partial-implementation.html">Random Forest</a></li>
<li class="nav-header">Classification Examples</li>
- <li><a href="/users/mapreduce/classification/breiman-example.html">Breiman example</a></li>
- <li><a href="/users/mapreduce/classification/twenty-newsgroups.html">20 newsgroups example</a></li>
+ <li><a href="/users/classification/breiman-example.html">Breiman example</a></li>
+ <li><a href="/users/classification/twenty-newsgroups.html">20 newsgroups example</a></li>
<li class="nav-header">Clustering</li>
- <li><a href="/users/mapreduce/clustering/k-means-clustering.html">k-Means</a></li>
- <li><a href="/users/mapreduce/clustering/canopy-clustering.html">Canopy</a></li>
- <li><a href="/users/mapreduce/clustering/fuzzy-k-means.html">Fuzzy k-Means</a></li>
- <li><a href="/users/mapreduce/clustering/streaming-k-means.html">Streaming KMeans</a></li>
- <li><a href="/users/mapreduce/clustering/spectral-clustering.html">Spectral Clustering</a></li>
+ <li><a href="/users/clustering/k-means-clustering.html">k-Means</a></li>
+ <li><a href="/users/clustering/canopy-clustering.html">Canopy</a></li>
+ <li><a href="/users/clustering/fuzzy-k-means.html">Fuzzy k-Means</a></li>
+ <li><a href="/users/clustering/streaming-k-means.html">Streaming KMeans</a></li>
+ <li><a href="/users/clustering/spectral-clustering.html">Spectral Clustering</a></li>
<li class="nav-header">Clustering Commandline usage</li>
- <li><a href="/users/mapreduce/clustering/k-means-commandline.html">Options for k-Means</a></li>
- <li><a href="/users/mapreduce/clustering/canopy-commandline.html">Options for Canopy</a></li>
- <li><a href="/users/mapreduce/clustering/fuzzy-k-means-commandline.html">Options for Fuzzy k-Means</a></li>
+ <li><a href="/users/clustering/k-means-commandline.html">Options for k-Means</a></li>
+ <li><a href="/users/clustering/canopy-commandline.html">Options for Canopy</a></li>
+ <li><a href="/users/clustering/fuzzy-k-means-commandline.html">Options for Fuzzy k-Means</a></li>
<li class="nav-header">Clustering Examples</li>
- <li><a href="/users/mapreduce/clustering/clustering-of-synthetic-control-data.html">Synthetic data</a></li>
+ <li><a href="/users/clustering/clustering-of-synthetic-control-data.html">Synthetic data</a></li>
<li class="nav-header">Cluster Post processing</li>
- <li><a href="/users/mapreduce/clustering/cluster-dumper.html">Cluster Dumper tool</a></li>
- <li><a href="/users/mapreduce/clustering/visualizing-sample-clusters.html">Cluster visualisation</a></li>
+ <li><a href="/users/clustering/cluster-dumper.html">Cluster Dumper tool</a></li>
+ <li><a href="/users/clustering/visualizing-sample-clusters.html">Cluster visualisation</a></li>
<li class="nav-header">Recommendations</li>
- <li><a href="/users/mapreduce/recommender/quickstart.html">Quickstart</a></li>
- <li><a href="/users/mapreduce/recommender/recommender-first-timer-faq.html">First Timer FAQ</a></li>
- <li><a href="/users/mapreduce/recommender/userbased-5-minutes.html">A user-based recommender <br/>in 5 minutes</a></li>
- <li><a href="/users/mapreduce/recommender/matrix-factorization.html">Matrix factorization-based<br/> recommenders</a></li>
- <li><a href="/users/mapreduce/recommender/recommender-documentation.html">Overview</a></li>
- <li><a href="/users/mapreduce/recommender/intro-itembased-hadoop.html">Intro to item-based recommendations<br/> with Hadoop</a></li>
- <li><a href="/users/mapreduce/recommender/intro-als-hadoop.html">Intro to ALS recommendations<br/> with Hadoop</a></li>
+ <li><a href="/users/recommender/quickstart.html">Quickstart</a></li>
+ <li><a href="/users/recommender/recommender-first-timer-faq.html">First Timer FAQ</a></li>
+ <li><a href="/users/recommender/userbased-5-minutes.html">A user-based recommender <br/>in 5 minutes</a></li>
+ <li><a href="/users/recommender/matrix-factorization.html">Matrix factorization-based<br/> recommenders</a></li>
+ <li><a href="/users/recommender/recommender-documentation.html">Overview</a></li>
+ <li><a href="/users/recommender/intro-itembased-hadoop.html">Intro to item-based recommendations<br/> with Hadoop</a></li>
+ <li><a href="/users/recommender/intro-als-hadoop.html">Intro to ALS recommendations<br/> with Hadoop</a></li>
</ul>
</li>
<!-- <li class="dropdown"> <a href="#" class="dropdown-toggle" data-toggle="dropdown">Recommendations<b class="caret"></b></a>