[mlpack-git] master: A page listing the man page documentation. Next I'll have to figure out how to autogenerate that. (1c0b5c2)

Fri Mar 27 20:56:09 EDT 2015

Repository : https://github.com/mlpack/mlpack.org

On branch  : master
Link       : https://github.com/mlpack/mlpack.org/compare/3170bd8210933684dc2519b6eab98a7243020f7c...1c0b5c2c8d782893d67b186467d905800368961c

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commit 1c0b5c2c8d782893d67b186467d905800368961c
Author: Ryan Curtin <ryan at ratml.org>
Date:   Sat Mar 28 00:55:46 2015 +0000

    A page listing the man page documentation.
    Next I'll have to figure out how to autogenerate that.


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1c0b5c2c8d782893d67b186467d905800368961c
 man.html | 109 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 109 insertions(+)

diff --git a/man.html b/man.html
new file mode 100644
index 0000000..f375876
--- /dev/null
+++ b/man.html
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+<html>
+<head>
+<!-- probably could use more keywords -->
+<meta name="keywords" content="mlpack, libmlpack, c++, armadillo, machine
+learning, data mining, classification, regression, tree-based methods, dual-tree
+algorithm">
+<meta name="description" content="mlpack: a scalable c++ machine learning
+library">
+<meta http-equiv="content-type" content="text/html; charset=UTF-8">
+<title>mlpack: a scalable c++ machine learning library</title>
+</head>
+<link rel="stylesheet" href="style.css">
+<link href='http://fonts.googleapis.com/css?family=Maven+Pro:500'
+rel='stylesheet' type='text/css'>
+<body>
+<!-- very simple table with as few words as possible -->
+<br>
+<div class="titlebar">
+   <a href="http://www.mlpack.org"><img src="mlpack.png"></a>
+</div>
+<center>
+<div class="mlnavbar">
+  <div class="navcontainer">
+   <div class="mlnavsel" name="mlnavmain"><a href="index.html">main</a></div>
+   <div class="mlnavitem" name="mlnavabout"><a href="about.html">about</a></div>
+   <div class="mlnavsel" name="mlnavdoc"><font
+class="whitebold">docs</font></div>
+   <div class="mlnavitem" name="mlnavhelp"><a href="help.html">get
+help</a></div>
+   <div class="mlnavitem" name="mlnavbugs"><a
+href="https://github.com/mlpack/mlpack">github</a></div>
+  </div>
+</div>
+</center>
+<div class="separator"></div>
+<center>
+<div class="mainsection smallertext">
+<p><font class="whitebold">mlpack</font> provides command-line executables for many
+of the algorithms it implements.  These may be used to perform many machine
+learning tasks without the overhead of writing C++, or may be used as part of a
+larger machine learning solution.</p>
+<p>Below is a list of the command-line executables <font
+class="whitebold">mlpack</font> provides, with links to the documentation for
+each executable.  This documentation may also be accessed with the <font
+class="code">--help</font> parameter or through the man pages provided with your
+distribution of <font class="whitebold">mlpack</font>.</p>
+<ul class="mainpage">
+<li><a href="man/allknn.html" class="manlink">allknn</a><font class="gray">: all <i>k</i>-nearest
+neighbor search with trees</font></li>
+<li><a href="man/allkfn.html" class="manlink">allkfn</a><font class="gray">: all <i>k</i>-furthest
+neighbor search with trees</font></li>
+<li><a href="man/allkrann.html" class="manlink">allkrann</a><font class="gray">: rank-approximate
+<i>k</i>-nearest neighbor search with trees</font></li>
+<li><a href="man/cf.html" class="manlink">cf</a><font class="gray">: generate recommendations via
+collaborative filtering</font></li>
+<li><a href="man/decision_stump.html" class="manlink">decision_stump</a><font class="gray">:
+classify with a decision stump</font></li>
+<li><a href="man/det.html" class="manlink">det</a><font class="gray">: density estimation
+trees</font></li>
+<li><a href="man/emst.html" class="manlink">emst</a><font class="gray">: calculate a Euclidean
+minimum spanning tree</font></li>
+<li><a href="man/fastmks.html" class="manlink">fastmks</a><font class="gray">: perform fast
+max-kernel search with trees</font></li>
+<li><a href="man/gmm.html" class="manlink">gmm</a><font class="gray">: train or classify with a
+Gaussian mixture model</font></li>
+<li><a href="man/hmm_generate.html" class="manlink">hmm_generate</a><font class="gray">: generate
+observations from a hidden Markov model (HMM)</font></li>
+<li><a href="man/hmm_loglik.html" class="manlink">hmm_loglik</a><font class="gray">: calculate the
+log-likelihood of some observations from an HMM</font></li>
+<li><a href="man/hmm_train.html" class="manlink">hmm_train</a><font class="gray">: train a hidden
+Markov model (HMM)</font></li>
+<li><a href="man/hmm_viterbi.html" class="manlink">hmm_viterbi</a><font class="gray">: find the
+most probable hidden states in an HMM for some observations</font></li>
+<li><a href="man/kernel_pca.html" class="manlink">kernel_pca</a><font class="gray">: perform kernel
+principal components analysis</font></li>
+<li><a href="man/kmeans.html" class="manlink">kmeans</a><font class="gray">: perform <i>k</i>-means
+clustering</font></li>
+<li><a href="man/lars.html" class="manlink">lars</a><font class="gray">: least-angle
+regression</font></li>
+<li><a href="man/linear_regression.html" class="manlink">linear_regression</a><font class="gray">:
+simple least-squares linear regression</font></li>
+<li><a href="man/local_coordinate_coding.html"
+class="manlink">local_coordinate_coding</a><font class="gray">: local coordinate
+coding</font></li>
+<li><a href="man/logistic_regression.html"
+class="manlink">logistic_regression</a><font class="gray">: train or classify with logistic
+regression</font></li>
+<li><a href="man/lsh.html" class="manlink">lsh</a><font class="gray">: approximate <i>k</i>-nearest
+neighbor search with locality-sensitive hashing</font></li>
+<li><a href="man/nbc.html" class="manlink">nbc</a><font class="gray">: train or classify with the
+naive Bayes classifier</font></li>
+<li><a href="man/nca.html" class="manlink">nca</a><font class="gray">: neighborhood components
+analysis</font></li>
+<li><a href="man/nmf.html" class="manlink">nmf</a><font class="gray">: non-negative matrix
+factorization</font></li>
+<li><a href="man/pca.html" class="manlink">pca</a><font class="gray">: principal components
+analysis</font></li>
+<li><a href="man/perceptron.html" class="manlink">perceptron</a><font class="gray">: train or
+classify with a perceptron</font></li>
+<li><a href="man/radical.html" class="manlink">radical</a><font class="gray">: RADICAL (independent
+components analysis)</font></li>
+<li><a href="man/range_search.html" class="manlink">range_search</a><font class="gray">: range
+search with trees</font></li>
+<li><a href="man/sparse_coding.html" class="manlink">sparse_coding</a><font class="gray">: sparse
+coding with dictionary learning</font></li>
+</ul>
+</div>
+</body>
+</html>

