ad102af169
## What changes were proposed in this pull request? This issue fixes all broken links on Spark 2.0 preview MLLib documents. Also, this contains some editorial change. **Fix broken links** * mllib-data-types.md * mllib-decision-tree.md * mllib-ensembles.md * mllib-feature-extraction.md * mllib-pmml-model-export.md * mllib-statistics.md **Fix malformed section header and scala coding style** * mllib-linear-methods.md **Replace indirect forward links with direct one** * ml-classification-regression.md ## How was this patch tested? Manual tests (with `cd docs; jekyll build`.) Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13608 from dongjoon-hyun/SPARK-15883.
60 lines
2 KiB
Markdown
60 lines
2 KiB
Markdown
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layout: global
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title: PMML model export - spark.mllib
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displayTitle: PMML model export - spark.mllib
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---
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* Table of contents
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{:toc}
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## `spark.mllib` supported models
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`spark.mllib` supports model export to Predictive Model Markup Language ([PMML](http://en.wikipedia.org/wiki/Predictive_Model_Markup_Language)).
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The table below outlines the `spark.mllib` models that can be exported to PMML and their equivalent PMML model.
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<table class="table">
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<thead>
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<tr><th>`spark.mllib` model</th><th>PMML model</th></tr>
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</thead>
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<tbody>
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<tr>
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<td>KMeansModel</td><td>ClusteringModel</td>
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</tr>
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<tr>
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<td>LinearRegressionModel</td><td>RegressionModel (functionName="regression")</td>
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</tr>
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<tr>
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<td>RidgeRegressionModel</td><td>RegressionModel (functionName="regression")</td>
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</tr>
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<tr>
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<td>LassoModel</td><td>RegressionModel (functionName="regression")</td>
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</tr>
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<tr>
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<td>SVMModel</td><td>RegressionModel (functionName="classification" normalizationMethod="none")</td>
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</tr>
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<tr>
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<td>Binary LogisticRegressionModel</td><td>RegressionModel (functionName="classification" normalizationMethod="logit")</td>
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</tr>
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</tbody>
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</table>
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## Examples
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<div class="codetabs">
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<div data-lang="scala" markdown="1">
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To export a supported `model` (see table above) to PMML, simply call `model.toPMML`.
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As well as exporting the PMML model to a String (`model.toPMML` as in the example above), you can export the PMML model to other formats.
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Refer to the [`KMeans` Scala docs](api/scala/index.html#org.apache.spark.mllib.clustering.KMeans) and [`Vectors` Scala docs](api/scala/index.html#org.apache.spark.mllib.linalg.Vectors$) for details on the API.
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Here a complete example of building a KMeansModel and print it out in PMML format:
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{% include_example scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala %}
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For unsupported models, either you will not find a `.toPMML` method or an `IllegalArgumentException` will be thrown.
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</div>
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</div>
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