index (MAHOUT) edited by Grant Ingersoll
Page: http://cwiki.apache.org/confluence/display/MAHOUT/index
Changes:
http://cwiki.apache.org/confluence/pages/diffpagesbyversion.action?pageId=74539&originalVersion=15&revisedVersion=16
Content:
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h1. Apache Mahout Wiki
Apache Mahout is a new Lucene TLP project to create scalable, machine learning
algorithms under the Apache license. For more information on the project goals
please see the [original
proposal|http://ml-site.grantingersoll.com/index.php?title=Incubator_proposal].
{toc:style=disc|minlevel=2}
h2. Historical Information
Project inspiration and formulation can be found at
[http://ml-site.grantingersoll.com]
h2. General
[TODO]
[FAQ]
[HowToContribute]
[Hadoop|http://hadoop.apache.org]
h2. Design
[Collection(De-)Serialization]
[Matrix Needs]
h2. 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]
h3. Classification
[Logistic Regression]
[NaiveBayes]
[Support Vector Machines] (SVM)
[Neural Network]
h3. Clustering
[k-Means]
[Expectation Maximization] (EM)
h3. Regression
[Locally Weighted Linear Regression]
h3. Dimension reduction
[Principal Components Analysis ] (PCA)
[Independent Component Analysis]
[Gaussian Discriminative Analysis] (GDA)
h3. Non map reduce 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.
[Hidden Markov Models] (HMM)
[Recommendation Learning]
h2. Collections/DataSets
[theinfo|http://theinfo.org/]
h2. Community
[MailingListArchives]
h2. Committer's Resources
[HowToUpdateTheWebsite]
[PatchCheckList]
[ReleaseToDo]
h3. Other Resources
[Committer's FAQ|http://www.apache.org/dev/committers.html]
[Apache Dev|http://www.apache.org/dev/]
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