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Replace example code in mllib-pmml-model-export.md using include_example https://issues.apache.org/jira/browse/SPARK-13018 The example code in the user guide is embedded in the markdown and hence it is not easy to test. It would be nice to automatically test them. This JIRA is to discuss options to automate example code testing and see what we can do in Spark 1.6. Goal is to move actual example code to spark/examples and test compilation in Jenkins builds. Then in the markdown, we can reference part of the code to show in the user guide. This requires adding a Jekyll tag that is similar to https://github.com/jekyll/jekyll/blob/master/lib/jekyll/tags/include.rb, e.g., called include_example. `{% include_example scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala %}` Jekyll will find `examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala` and pick code blocks marked "example" and replace code block in `{% highlight %}` in the markdown. See more sub-tasks in parent ticket: https://issues.apache.org/jira/browse/SPARK-11337 Author: Xin Ren <iamshrek@126.com> Closes #11126 from keypointt/SPARK-13018.
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| layout | title | displayTitle |
|---|---|---|
| global | PMML model export - spark.mllib | PMML model export - spark.mllib |
- Table of contents {:toc}
spark.mllib supported models
spark.mllib supports model export to Predictive Model Markup Language (PMML).
The table below outlines the spark.mllib models that can be exported to PMML and their equivalent PMML model.
| `spark.mllib` model | PMML model |
|---|---|
| KMeansModel | ClusteringModel |
| LinearRegressionModel | RegressionModel (functionName="regression") |
| RidgeRegressionModel | RegressionModel (functionName="regression") |
| LassoModel | RegressionModel (functionName="regression") |
| SVMModel | RegressionModel (functionName="classification" normalizationMethod="none") |
| Binary LogisticRegressionModel | RegressionModel (functionName="classification" normalizationMethod="logit") |
Examples
To export a supported `model` (see table above) to PMML, simply call `model.toPMML`.
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.
Refer to the KMeans Scala docs and Vectors Scala docs for details on the API.
Here a complete example of building a KMeansModel and print it out in PMML format: {% include_example scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala %}
For unsupported models, either you will not find a .toPMML method or an IllegalArgumentException will be thrown.