[jira] [Commented] (SPARK-6258) Python MLlib API missing items: Clustering

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-6258?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14517470#comment-14517470 ] 

Joseph K. Bradley commented on SPARK-6258:
------------------------------------------

About a question asked offline:
{quote}How can you pass the GaussianMixtureModel object to the trainGaussianMixture method in PythonMLlibAPI.scala?{quote}
It's better to pass simple objects such as native types (float, int, etc.) or basic data structures (arrays, etc.).  For this task, only parameters need to be passed, which can be done following the many other examples in PythonMLLibAPI.scala.  If you had to pass a complex object, it would be best to deconstruct it into simple types.

> Python MLlib API missing items: Clustering
> ------------------------------------------
>
>                 Key: SPARK-6258
>                 URL: https://issues.apache.org/jira/browse/SPARK-6258
>             Project: Spark
>          Issue Type: Sub-task
>          Components: MLlib, PySpark
>    Affects Versions: 1.3.0
>            Reporter: Joseph K. Bradley
>
> This JIRA lists items missing in the Python API for this sub-package of MLlib.
> This list may be incomplete, so please check again when sending a PR to add these features to the Python API.
> Also, please check for major disparities between documentation; some parts of the Python API are less well-documented than their Scala counterparts.  Some items may be listed in the umbrella JIRA linked to this task.
> KMeans
> * setEpsilon
> * setInitializationSteps
> KMeansModel
> * computeCost
> * k
> GaussianMixture
> * setInitialModel
> GaussianMixtureModel
> * k
> Completely missing items which should be fixed in separate JIRAs (which have been created and linked to the umbrella JIRA)
> * LDA
> * PowerIterationClustering
> * StreamingKMeans



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