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https://issues.apache.org/jira/browse/SPARK-13097?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15124323#comment-15124323
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Apache Spark commented on SPARK-13097:
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User 'seddonm1' has created a pull request for this issue:
https://github.com/apache/spark/pull/10976
> Extend Binarizer to allow Double AND Vector inputs
> --------------------------------------------------
>
> Key: SPARK-13097
> URL: https://issues.apache.org/jira/browse/SPARK-13097
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Mike Seddon
> Priority: Minor
>
> To enhance the existing SparkML Binarizer [SPARK-5891] to allow Vector in
> addition to the existing Double input column type.
> A use case for this enhancement is for when a user wants to Binarize many
> similar feature columns at once using the same threshold value.
> A real-world example for this would be where the authors of one of the
> leading MNIST handwriting character recognition entries converts 784
> grayscale (0-255) pixels (28x28 pixel images) to binary if the pixel's
> grayscale exceeds 127.5: (http://arxiv.org/abs/1003.0358). With this
> modification the user is able to: VectorAssembler(784
> columns)->Binarizer(127.5)->Classifier as all the pixels are of a similar
> type.
> This approach also allows much easier use of the ParamGridBuilder to test
> multiple theshold values.
> I have already written the code and unit tests and have tested in a
> Multilayer perceptron classifier workflow.
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