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author | Reynold Xin <rxin@apache.org> | 2015-09-17 22:07:42 +0000 |
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committer | Reynold Xin <rxin@apache.org> | 2015-09-17 22:07:42 +0000 |
commit | ee9ffe89d608e7640a2487406b618d27e58026d6 (patch) | |
tree | 50ec819abb41a9a769d7f64eed1f0ab2084aa6ff /site/docs/1.5.0/mllib-pmml-model-export.html | |
parent | c7104724b279f09486ea62f4a24252e8d06f5c96 (diff) | |
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delete 1.5.0
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diff --git a/site/docs/1.5.0/mllib-pmml-model-export.html b/site/docs/1.5.0/mllib-pmml-model-export.html deleted file mode 100644 index f5e406dd3..000000000 --- a/site/docs/1.5.0/mllib-pmml-model-export.html +++ /dev/null @@ -1,245 +0,0 @@ -<!DOCTYPE html> -<!--[if lt IE 7]> <html class="no-js lt-ie9 lt-ie8 lt-ie7"> <![endif]--> -<!--[if IE 7]> <html class="no-js lt-ie9 lt-ie8"> <![endif]--> -<!--[if IE 8]> <html class="no-js lt-ie9"> <![endif]--> -<!--[if gt IE 8]><!--> <html class="no-js"> <!--<![endif]--> - <head> - <meta charset="utf-8"> - <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> - <title>PMML model export - MLlib - Spark 1.5.0 Documentation</title> - - - - - <link rel="stylesheet" href="css/bootstrap.min.css"> - <style> - body { - padding-top: 60px; - padding-bottom: 40px; - } - </style> - <meta name="viewport" content="width=device-width"> - <link rel="stylesheet" href="css/bootstrap-responsive.min.css"> - <link rel="stylesheet" href="css/main.css"> - - <script src="js/vendor/modernizr-2.6.1-respond-1.1.0.min.js"></script> - - <link rel="stylesheet" href="css/pygments-default.css"> - - - <!-- Google analytics script --> - <script type="text/javascript"> - var _gaq = _gaq || []; - _gaq.push(['_setAccount', 'UA-32518208-2']); - _gaq.push(['_trackPageview']); - - (function() { - var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; - ga.src = ('https:' == document.location.protocol ? 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<li><a href="hardware-provisioning.html">Hardware Provisioning</a></li> - <li><a href="hadoop-third-party-distributions.html">3<sup>rd</sup>-Party Hadoop Distros</a></li> - <li class="divider"></li> - <li><a href="building-spark.html">Building Spark</a></li> - <li><a href="https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark">Contributing to Spark</a></li> - <li><a href="https://cwiki.apache.org/confluence/display/SPARK/Supplemental+Spark+Projects">Supplemental Projects</a></li> - </ul> - </li> - </ul> - <!--<p class="navbar-text pull-right"><span class="version-text">v1.5.0</span></p>--> - </div> - </div> - </div> - - <div class="container" id="content"> - - <h1 class="title"><a href="mllib-guide.html">MLlib</a> - PMML model export</h1> - - - <ul id="markdown-toc"> - <li><a href="#mllib-supported-models">MLlib supported models</a></li> - <li><a href="#examples">Examples</a></li> -</ul> - -<h2 id="mllib-supported-models">MLlib supported models</h2> - -<p>MLlib supports model export to Predictive Model Markup Language (<a href="http://en.wikipedia.org/wiki/Predictive_Model_Markup_Language">PMML</a>).</p> - -<p>The table below outlines the MLlib models that can be exported to PMML and their equivalent PMML model.</p> - -<table class="table"> - <thead> - <tr><th>MLlib model</th><th>PMML model</th></tr> - </thead> - <tbody> - <tr> - <td>KMeansModel</td><td>ClusteringModel</td> - </tr> - <tr> - <td>LinearRegressionModel</td><td>RegressionModel (functionName="regression")</td> - </tr> - <tr> - <td>RidgeRegressionModel</td><td>RegressionModel (functionName="regression")</td> - </tr> - <tr> - <td>LassoModel</td><td>RegressionModel (functionName="regression")</td> - </tr> - <tr> - <td>SVMModel</td><td>RegressionModel (functionName="classification" normalizationMethod="none")</td> - </tr> - <tr> - <td>Binary LogisticRegressionModel</td><td>RegressionModel (functionName="classification" normalizationMethod="logit")</td> - </tr> - </tbody> -</table> - -<h2 id="examples">Examples</h2> -<div class="codetabs"> - -<div data-lang="scala"> - <p>To export a supported <code>model</code> (see table above) to PMML, simply call <code>model.toPMML</code>.</p> - - <p>Here a complete example of building a KMeansModel and print it out in PMML format:</p> - - <div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">import</span> <span class="nn">org.apache.spark.mllib.clustering.KMeans</span> -<span class="k">import</span> <span class="nn">org.apache.spark.mllib.linalg.Vectors</span> - -<span class="c1">// Load and parse the data</span> -<span class="k">val</span> <span class="n">data</span> <span class="k">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">textFile</span><span class="o">(</span><span class="s">"data/mllib/kmeans_data.txt"</span><span class="o">)</span> -<span class="k">val</span> <span class="n">parsedData</span> <span class="k">=</span> <span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">s</span> <span class="k">=></span> <span class="nc">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="o">(</span><span class="n">s</span><span class="o">.</span><span class="n">split</span><span class="o">(</span><span class="sc">' '</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">toDouble</span><span class="o">))).</span><span class="n">cache</span><span class="o">()</span> - -<span class="c1">// Cluster the data into two classes using KMeans</span> -<span class="k">val</span> <span class="n">numClusters</span> <span class="k">=</span> <span class="mi">2</span> -<span class="k">val</span> <span class="n">numIterations</span> <span class="k">=</span> <span class="mi">20</span> -<span class="k">val</span> <span class="n">clusters</span> <span class="k">=</span> <span class="nc">KMeans</span><span class="o">.</span><span class="n">train</span><span class="o">(</span><span class="n">parsedData</span><span class="o">,</span> <span class="n">numClusters</span><span class="o">,</span> <span class="n">numIterations</span><span class="o">)</span> - -<span class="c1">// Export to PMML</span> -<span class="n">println</span><span class="o">(</span><span class="s">"PMML Model:\n"</span> <span class="o">+</span> <span class="n">clusters</span><span class="o">.</span><span class="n">toPMML</span><span class="o">)</span></code></pre></div> - - <p>As well as exporting the PMML model to a String (<code>model.toPMML</code> as in the example above), you can export the PMML model to other formats:</p> - - <div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="c1">// Export the model to a String in PMML format</span> -<span class="n">clusters</span><span class="o">.</span><span class="n">toPMML</span> - -<span class="c1">// Export the model to a local file in PMML format</span> -<span class="n">clusters</span><span class="o">.</span><span class="n">toPMML</span><span class="o">(</span><span class="s">"/tmp/kmeans.xml"</span><span class="o">)</span> - -<span class="c1">// Export the model to a directory on a distributed file system in PMML format</span> -<span class="n">clusters</span><span class="o">.</span><span class="n">toPMML</span><span class="o">(</span><span class="n">sc</span><span class="o">,</span><span class="s">"/tmp/kmeans"</span><span class="o">)</span> - -<span class="c1">// Export the model to the OutputStream in PMML format</span> -<span class="n">clusters</span><span class="o">.</span><span class="n">toPMML</span><span class="o">(</span><span class="nc">System</span><span class="o">.</span><span class="n">out</span><span class="o">)</span></code></pre></div> - 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