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https://issues.apache.org/jira/browse/SPARK-6261?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14381087#comment-14381087
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Joseph K. Bradley commented on SPARK-6261:
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{quote}
StandardScalerModel seems to have no method named predict()
{quote}
-> Yes, since it's a transformer instead of a normal ML "model," it has a
transform() method instead.
{quote}
Are we supposed to wrap other methods implemented in StandardScalerModel?
{quote}
-> It could be implemented either (a) by wrapping each method or (b) by storing
the model itself in Python and implementing the methods in Python. Option (a)
will probably be easier since there are already helper method in Python for
calling JVM methods. (See how "transform" is called in JavaVectorTransformer.)
Let's do these items 1 at a time. Could you please create a JIRA for the model
you want to update? I can then link it to this JIRA. Thanks!
> Python MLlib API missing items: Feature
> ---------------------------------------
>
> Key: SPARK-6261
> URL: https://issues.apache.org/jira/browse/SPARK-6261
> 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.
> StandardScalerModel
> * All functionality except predict() is missing.
> IDFModel
> * idf
> Word2Vec
> * setMinCount
> Word2VecModel
> * getVectors
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