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Posted to commits@mahout.apache.org by sr...@apache.org on 2012/07/12 11:26:03 UTC
svn commit: r1360593 [1/17] - in /mahout/site/trunk: ./ cgi-bin/ content/
content/attachments/ content/attachments/101992/
content/attachments/116559/ content/attachments/22872433/
content/attachments/22872443/ content/attachments/23335706/ content/att...
Author: srowen
Date: Thu Jul 12 09:25:54 2012
New Revision: 1360593
URL: http://svn.apache.org/viewvc?rev=1360593&view=rev
Log:
Commit new CMS-based port of wiki from Rahul
Added:
mahout/site/trunk/
mahout/site/trunk/cgi-bin/
mahout/site/trunk/content/
mahout/site/trunk/content/05.mdtext
mahout/site/trunk/content/1.mdtext
mahout/site/trunk/content/20newsgroups.mdtext
mahout/site/trunk/content/algorithm-summary-table.mdtext
mahout/site/trunk/content/algorithms.mdtext
mahout/site/trunk/content/asfemail.mdtext
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mahout/site/trunk/content/bayesian-commandline.mdtext
mahout/site/trunk/content/bayesian.mdtext
mahout/site/trunk/content/books-tutorials-and-talks.mdtext
mahout/site/trunk/content/boosting.mdtext
mahout/site/trunk/content/breiman-example.mdtext
mahout/site/trunk/content/buildingmahout.mdtext
mahout/site/trunk/content/canopy-clustering.mdtext
mahout/site/trunk/content/canopy-commandline.mdtext
mahout/site/trunk/content/class-discovery.mdtext
mahout/site/trunk/content/classifyingyourdata.mdtext
mahout/site/trunk/content/cluster-dumper.mdtext
mahout/site/trunk/content/clustering-of-synthetic-control-data.mdtext
mahout/site/trunk/content/clustering-seinfeld-episodes.mdtext
mahout/site/trunk/content/clusteringyourdata.mdtext
mahout/site/trunk/content/collaborative-filtering-with-als-wr.mdtext
mahout/site/trunk/content/collections.mdtext
mahout/site/trunk/content/collocations.mdtext
mahout/site/trunk/content/complementary-naive-bayes.mdtext
mahout/site/trunk/content/converting-content.mdtext
mahout/site/trunk/content/creating-vectors-from-text.mdtext
mahout/site/trunk/content/creating-vectors.mdtext
mahout/site/trunk/content/data-formats.mdtext
mahout/site/trunk/content/data-processing.mdtext
mahout/site/trunk/content/database-integrations.mdtext
mahout/site/trunk/content/developer-resources.mdtext
mahout/site/trunk/content/dimensional-reduction.mdtext
mahout/site/trunk/content/dirichlet-commandline.mdtext
mahout/site/trunk/content/dirichlet-process-clustering.mdtext
mahout/site/trunk/content/downloads.mdtext
mahout/site/trunk/content/expectation-maximization.mdtext
mahout/site/trunk/content/faq.mdtext
mahout/site/trunk/content/file-format-integrations.mdtext
mahout/site/trunk/content/fuzzy-k-means-commandline.mdtext
mahout/site/trunk/content/fuzzy-k-means.mdtext
mahout/site/trunk/content/gaussian-discriminative-analysis.mdtext
mahout/site/trunk/content/glossary.mdtext
mahout/site/trunk/content/gsoc.mdtext
mahout/site/trunk/content/hidden-markov-models.mdtext
mahout/site/trunk/content/hierarchical-clustering.mdtext
mahout/site/trunk/content/how-do-mahout-refresh-from-database?.mdtext
mahout/site/trunk/content/how-to-become-a-committer.mdtext
mahout/site/trunk/content/how-to-contribute.mdtext
mahout/site/trunk/content/how-to-release.mdtext
mahout/site/trunk/content/how-to-update-the-website.mdtext
mahout/site/trunk/content/images/
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mahout/site/trunk/content/independent-component-analysis.mdtext
mahout/site/trunk/content/issue-tracker.mdtext
mahout/site/trunk/content/itembased-collaborative-filtering.mdtext
mahout/site/trunk/content/k-means-clustering.mdtext
mahout/site/trunk/content/k-means-commandline.mdtext
mahout/site/trunk/content/latent-dirichlet-allocation.mdtext
mahout/site/trunk/content/lda-commandline.mdtext
mahout/site/trunk/content/llr---log-likelihood-ratio.mdtext
mahout/site/trunk/content/locally-weighted-linear-regression.mdtext
mahout/site/trunk/content/logistic-regression.mdtext
mahout/site/trunk/content/machine-learning-resources.mdtext
mahout/site/trunk/content/mahout-benchmarks.mdtext
mahout/site/trunk/content/mahout-collections.mdtext
mahout/site/trunk/content/mahout-on-amazon-ec2.mdtext
mahout/site/trunk/content/mahout-on-elastic-mapreduce.mdtext
mahout/site/trunk/content/mahout-project.mdtext
mahout/site/trunk/content/mahout-wiki.mdtext
mahout/site/trunk/content/mahout.ga.tutorial.mdtext
mahout/site/trunk/content/mahoutintegration.mdtext
mahout/site/trunk/content/mahoutname.mdtext
mahout/site/trunk/content/mailing-lists,-irc-and-archives.mdtext
mahout/site/trunk/content/matrix-and-vector-needs.mdtext
mahout/site/trunk/content/mean-shift-clustering.mdtext
mahout/site/trunk/content/mean-shift-commandline.mdtext
mahout/site/trunk/content/minhash-clustering.mdtext
mahout/site/trunk/content/mr---map-reduce.mdtext
mahout/site/trunk/content/naivebayes.mdtext
mahout/site/trunk/content/neural-network.mdtext
mahout/site/trunk/content/online-passive-aggressive.mdtext
mahout/site/trunk/content/online-viterbi.mdtext
mahout/site/trunk/content/overview.mdtext
mahout/site/trunk/content/parallel-frequent-pattern-mining.mdtext
mahout/site/trunk/content/parallel-viterbi.mdtext
mahout/site/trunk/content/partial-implementation.mdtext
mahout/site/trunk/content/patch-check-list.mdtext
mahout/site/trunk/content/pearsoncorrelation.mdtext
mahout/site/trunk/content/perceptron-and-winnow.mdtext
mahout/site/trunk/content/please-remove-this-page.mdtext
mahout/site/trunk/content/powered-by-mahout.mdtext
mahout/site/trunk/content/principal-components-analysis.mdtext
mahout/site/trunk/content/privacy-policy.mdtext
mahout/site/trunk/content/professional-support.mdtext
mahout/site/trunk/content/quick-tour-of-text-analysis-using-the-mahout-command-line.mdtext
mahout/site/trunk/content/quickstart.mdtext
mahout/site/trunk/content/random-forests.mdtext
mahout/site/trunk/content/recommendationexamples.mdtext
mahout/site/trunk/content/recommender-documentation.mdtext
mahout/site/trunk/content/recommender-first-timer-faq.mdtext
mahout/site/trunk/content/reference-reading.mdtext
mahout/site/trunk/content/restricted-boltzmann-machines.mdtext
mahout/site/trunk/content/rowsimilarityjob.mdtext
mahout/site/trunk/content/sample-clusters-animation.mdtext
mahout/site/trunk/content/spectral-clustering.mdtext
mahout/site/trunk/content/stochastic-singular-value-decomposition.mdtext
mahout/site/trunk/content/styles/
mahout/site/trunk/content/styles/site.css
mahout/site/trunk/content/support-vector-machines.mdtext
mahout/site/trunk/content/svd---singular-value-decomposition.mdtext
mahout/site/trunk/content/system-requirements.mdtext
mahout/site/trunk/content/tastecommandline.mdtext
mahout/site/trunk/content/testing.mdtext
mahout/site/trunk/content/tf-idf---term-frequency-inverse-document-frequency.mdtext
mahout/site/trunk/content/thirdparty-dependencies.mdtext
mahout/site/trunk/content/top-down-clustering.mdtext
mahout/site/trunk/content/traveling-salesman.mdtext
mahout/site/trunk/content/twenty-newsgroups.mdtext
mahout/site/trunk/content/use-an-existing-hadoop-ami.mdtext
mahout/site/trunk/content/using-mahout-with-python-via-jpype.mdtext
mahout/site/trunk/content/version-control.mdtext
mahout/site/trunk/content/viewing-result.mdtext
mahout/site/trunk/content/viewing-results.mdtext
mahout/site/trunk/content/visualize-classification-results.mdtext
mahout/site/trunk/content/visualizing-sample-clusters.mdtext
mahout/site/trunk/content/what-it-is-the-decision-forest-?-it-is-same-as-random-forest?.mdtext
mahout/site/trunk/content/who-we-are.mdtext
mahout/site/trunk/content/wikipedia-bayes-example.mdtext
mahout/site/trunk/lib/
mahout/site/trunk/lib/path.pm
mahout/site/trunk/lib/view.pm
mahout/site/trunk/templates/
mahout/site/trunk/templates/single_narrative.html
mahout/site/trunk/templates/skeleton.html
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+Title: 05
Added: mahout/site/trunk/content/1.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/trunk/content/1.mdtext?rev=1360593&view=auto
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+Title: 1
Added: mahout/site/trunk/content/20newsgroups.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/trunk/content/20newsgroups.mdtext?rev=1360593&view=auto
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+Title: 20Newsgroups
+<a name="20Newsgroups-NaiveBayesusing20NewsgroupsData"></a>
+# Naive Bayes using 20 Newsgroups Data
+
+See [https://issues.apache.org/jira/browse/MAHOUT-9](https://issues.apache.org/jira/browse/MAHOUT-9)
Added: mahout/site/trunk/content/algorithm-summary-table.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/trunk/content/algorithm-summary-table.mdtext?rev=1360593&view=auto
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+Title: Algorithm summary table
+<a name="Algorithmsummarytable-Classification"></a>
+### Classification
+
+<table>
+<tr><th> algorithm name </th><th> description </th><th> production-ready? </th><th> needs Hadoop? </th><th>
+input format </th><th> run command </th></tr>
+<tr><td> SGD LogisticRegression command line </td><td> train a logistic regression model
+with Stochastic Gradient Descent </td><td> x </td><td> </td><td> CSV with Header </td><td>
+trainAdaptiveLogistic </td></tr>
+<tr><td> SGD LogisticRegression API </td><td> train a logistic regression model with
+Stochastic Gradient Descent </td><td> x </td><td> </td><td> Mahout Vector, feature hashing API </td><td>
+custom code </td></tr>
+<tr><td> Random Forest </td><td> build a random forest </td><td> </td><td> x </td><td> CSV without header and
+quotes </td><td> BuildForest </td></tr>
+</table>
+
+<a name="Algorithmsummarytable-CollaborativeFiltering"></a>
+### Collaborative Filtering
+
+<table>
+<tr><th> algorithm name </th><th> description </th><th> production-ready? </th><th> needs Hadoop? </th><th>
+input format </th><th> run command </th></tr>
+<tr><td> Itembased Collaborative Filtering </td><td>compute pairwise item-similarities </td><td> x
+</td><td> x </td><td> tab-separated text files </td><td> itemsimilarity </td></tr>
+<tr><td> Itembased Collaborative Filtering </td><td> compute recommendations as batch </td><td> x
+</td><td> x </td><td> tab-separated text files </td><td> recommenditembased </td></tr>
+<tr><td> Matrix factorization with Alternating Least Squares </td><td> decompose a rating
+matrix </td><td> </td><td> x </td><td> tab-separated text files </td><td> parallelALS </td></tr>
+<tr><td> Matrix factorization </td><td> predict unknown preferences using decomposed
+rating matrix </td><td> x </td><td> x </td><td> tab-separated text files </td><td> predictFromFactorization
+ </td></tr>
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+Title: Algorithms
+<a name="Algorithms-Algorithms"></a>
+## Algorithms
+
+This section contains links to information, examples, use cases, etc. for
+the various algorithms we intend to implement. Click the individual links
+to learn more. The initial algorithms descriptions have been copied here
+from the original project proposal. The algorithms are grouped by the
+application setting, they can be used for. In case of multiple
+applications, the version presented in the paper was chosen, versions as
+implemented in our project will be added as soon as we are working on them.
+
+Original Paper: [Map Reduce for Machine Learning on Multicore](http://www.cs.stanford.edu/people/ang//papers/nips06-mapreducemulticore.pdf)
+
+Papers related to Map Reduce:
+* [Evaluating MapReduce for Multi-core and Multiprocessor Systems](http://csl.stanford.edu/~christos/publications/2007.cmp_mapreduce.hpca.pdf)
+* [Map Reduce: Distributed Computing for Machine Learning](http://www.icsi.berkeley.edu/~arlo/publications/gillick_cs262a_proj.pdf)
+
+For Papers, videos and books related to machine learning in general, see [Machine Learning Resources](machine-learning-resources.html)
+
+All algorithms are either marked as _integrated_, that is the
+implementation is integrated into the development version of Mahout.
+Algorithms that are currently being developed are annotated with a link to
+the JIRA issue that deals with the specific implementation. Usually these
+issues already contain patches that are more or less major, depending on
+how much work was spent on the issue so far. Algorithms that have so far
+not been touched are marked as _open_.
+
+[What, When, Where, Why (but not How or Who)](what,-when,-where,-why-(but-not-how-or-who).html)
+ \- Community tips, tricks, etc. for when to use which algorithm in what
+situations, what to watch out for in terms of errors. That is, practical
+advice on using Mahout for your problems.
+
+<a name="Algorithms-Classification"></a>
+### Classification
+
+A general introduction to the most common text classification algorithms
+can be found at Google Answers: [http://answers.google.com/answers/main?cmd=threadview&id=225316](http://answers.google.com/answers/main?cmd=threadview&id=225316)
+ For information on the algorithms implemented in Mahout (or scheduled for
+implementation) please visit the following pages.
+
+[Logistic Regression](logistic-regression.html)
+ (SGD)
+
+[Bayesian](bayesian.html)
+
+[Support Vector Machines](support-vector-machines.html)
+ (SVM) (open: [MAHOUT-14|http://issues.apache.org/jira/browse/MAHOUT-14]
+, [MAHOUT-232|http://issues.apache.org/jira/browse/MAHOUT-232]
+ and [MAHOUT-334|https://issues.apache.org/jira/browse/MAHOUT-334]
+)
+
+[Perceptron and Winnow](perceptron-and-winnow.html)
+ (open: [MAHOUT-85|http://issues.apache.org/jira/browse/MAHOUT-85]
+)
+
+[Neural Network](neural-network.html)
+ (open, but [MAHOUT-228|http://issues.apache.org/jira/browse/MAHOUT-228]
+ might help)
+
+[Random Forests](random-forests.html)
+ (integrated - [MAHOUT-122|http://issues.apache.org/jira/browse/MAHOUT-122]
+, [MAHOUT-140|http://issues.apache.org/jira/browse/MAHOUT-140]
+, [MAHOUT-145|http://issues.apache.org/jira/browse/MAHOUT-145]
+)
+
+[Restricted Boltzmann Machines](restricted-boltzmann-machines.html)
+ (open, [MAHOUT-375|http://issues.apache.org/jira/browse/MAHOUT-375]
+, GSOC2010)
+
+[Online Passive Aggressive](online-passive-aggressive.html)
+ (integrated, [MAHOUT-702|http://issues.apache.org/jira/browse/MAHOUT-702]
+)
+
+[Boosting](boosting.html)
+ (awaiting patch commit, [MAHOUT-716|https://issues.apache.org/jira/browse/MAHOUT-716]
+)
+
+[Hidden Markov Models](hidden-markov-models.html)
+ (HMM) (MAHOUT-627, MAHOUT-396, MAHOUT-734) - Training is done in
+Map-Reduce
+
+<a name="Algorithms-Clustering"></a>
+### Clustering
+
+[Reference Reading](reference-reading.html)
+
+[MAHOUT:Canopy Clustering](mahout:canopy-clustering.html)
+ ([MAHOUT-3|https://issues.apache.org/jira/browse/MAHOUT-3] - integrated)
+
+[K-Means Clustering](k-means-clustering.html)
+ ([MAHOUT-5|https://issues.apache.org/jira/browse/MAHOUT-5] - integrated)
+
+[Fuzzy K-Means](fuzzy-k-means.html)
+ ([MAHOUT-74|https://issues.apache.org/jira/browse/MAHOUT-74] - integrated)
+
+[Expectation Maximization](expectation-maximization.html)
+ (EM) ([MAHOUT-28|http://issues.apache.org/jira/browse/MAHOUT-28])
+
+[Mean Shift Clustering](mean-shift-clustering.html)
+ ([MAHOUT-15|https://issues.apache.org/jira/browse/MAHOUT-15] - integrated)
+
+[Hierarchical Clustering](hierarchical-clustering.html)
+ ([MAHOUT-19|http://issues.apache.org/jira/browse/MAHOUT-19])
+
+[Dirichlet Process Clustering](dirichlet-process-clustering.html)
+ ([MAHOUT-30|http://issues.apache.org/jira/browse/MAHOUT-30] - integrated)
+
+[Latent Dirichlet Allocation](latent-dirichlet-allocation.html)
+ ([MAHOUT-123|http://issues.apache.org/jira/browse/MAHOUT-123] -
+integrated)
+
+[Spectral Clustering](spectral-clustering.html)
+ ([MAHOUT-363|https://issues.apache.org/jira/browse/MAHOUT-363] -
+integrated)
+
+[Minhash Clustering](minhash-clustering.html)
+ ([MAHOUT-344|https://issues.apache.org/jira/browse/MAHOUT-344] -
+integrated)
+
+[Top Down Clustering](top-down-clustering.html)
+ ([MAHOUT-843|https://issues.apache.org/jira/browse/MAHOUT-843] -
+integrated)
+
+<a name="Algorithms-PatternMining"></a>
+### Pattern Mining
+
+[Parallel FP Growth Algorithm](parallel-frequent-pattern-mining.html)
+ (Also known as Frequent Itemset mining)
+
+<a name="Algorithms-Regression"></a>
+### Regression
+
+[Locally Weighted Linear Regression](locally-weighted-linear-regression.html)
+ (open)
+
+
+<a name="Algorithms-Dimensionreduction"></a>
+### Dimension reduction
+
+[Singular Value Decomposition and other Dimension Reduction Techniques](dimensional-reduction.html)
+ (available since 0.3)
+
+[Stochastic Singular Value Decomposition with PCA workflow](stochastic-singular-value-decomposition.html)
+ (PCA workflow now integrated)
+
+[Principal Components Analysis](principal-components-analysis.html)
+ (PCA) (open)
+
+[Independent Component Analysis](independent-component-analysis.html)
+ (open)
+
+[Gaussian Discriminative Analysis](gaussian-discriminative-analysis.html)
+ (GDA) (open)
+
+<a name="Algorithms-EvolutionaryAlgorithms"></a>
+### Evolutionary Algorithms
+
+see also: [MAHOUT-56 (integrated)](http://issues.apache.org/jira/browse/MAHOUT-56)
+
+You will find here information, examples, use cases, etc. related to
+Evolutionary Algorithms.
+
+Introductions and Tutorials:
+* [Evolutionary Algorithms Introduction](http://www.geatbx.com/docu/algindex.html)
+* [How to distribute the fitness evaluation using Mahout.GA](mahout.ga.tutorial.html)
+
+Examples:
+* [Traveling Salesman](traveling-salesman.html)
+* [Class Discovery](class-discovery.html)
+
+<a name="Algorithms-Recommenders/CollaborativeFiltering"></a>
+### Recommenders / Collaborative Filtering
+
+Mahout contains both simple non-distributed recommender implementations and
+distributed Hadoop-based recommenders.
+
+ * [Non-distributed recommenders ("Taste")](recommender-documentation.html)
+ (integrated)
+ * [Distributed Item-Based Collaborative Filtering](itembased-collaborative-filtering.html)
+ (integrated)
+ * [Collaborative Filtering using a parallel matrix factorization](collaborative-filtering-with-als-wr.html)
+ (integrated)
+ * [First-timer FAQ](recommender-first-timer-faq.html)
+
+<a name="Algorithms-VectorSimilarity"></a>
+### Vector Similarity
+
+Mahout contains implementations that allow one to compare one or more
+vectors with another set of vectors. This can be useful if one is, for
+instance, trying to calculate the pairwise similarity between all documents
+(or a subset of docs) in a corpus.
+
+* RowSimilarityJob -- Builds an inverted index and then computes distances
+between items that have co-occurrences. This is a fully distributed
+calculation.
+* VectorDistanceJob -- Does a map side join between a set of "seed" vectors
+and all of the input vectors.
+
+<a name="Algorithms-Other"></a>
+### Other
+
+ * [Collocations](collocations.html)
+
+<a name="Algorithms-Non-MapReducealgorithms"></a>
+### Non-MapReduce algorithms
+
+Some algorithms and applications appeared on the mailing list, that have
+not been published in map reduce form so far. As we do not restrict
+ourselves to Hadoop-only versions, these proposals are listed here.
+
+
+
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+Title: ASFEmail
+<a name="ASFEmail-Introduction"></a>
+# Introduction
+
+The ASF Email example demonstrate a variety of Mahout's capabilities using
+a single, publicly available (public domain) data set consisting of
+approximately 7 million emails from the Apache Software Foundation. The
+data set is currently hosted at Amazon as a public data set (it will cost
+you to download the set) available at
+http://aws.amazon.com/datasets/7791434387204566. A subset of the data can
+be retrieved at no cost from
+http://www.lucidimagination.com/devzone/technical-articles/scaling-mahout.
+
+http://www.ibm.com/developerworks/java/library/j-mahout-scaling/
+
+<a name="ASFEmail-Requirements"></a>
+# Requirements
+
+* You will need a trunk version (from [Subversion](http://svn.apache.org/repos/asf/mahout/trunk/)
+) of Mahout as of December 2011 (but you might as well get the latest),
+which is will eventually become Mahout 0.6.
+* Java 1.6
+* A local copy of the dataset.
+
+
+<a name="ASFEmail-Runningtheexamples"></a>
+# Running the examples
+
+All of the examples are contained in the
+$MAHOUT_HOME/examples/bin/asf-email-examples.sh.
+
+To run:
+
+
+ cd $MAHOUT_HOME/examples/bin
+ ./asf-email-examples.sh <PATH TO DIRECTORY CONTAINING EMAIL> <OUTPUT PATH>
+
+
+The script will then prompt you to make a series of selections depending on
+which example you wish to run.
+
+<a name="ASFEmail-Background"></a>
+# Background
+
+This example was developed as part of an article written for IBM
+developerWorks on [scaling Mahout](http://www.ibm.com/developerworks/java/library/j-mahout-scaling/)
+.
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