You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2016/02/16 05:16:18 UTC
[jira] [Resolved] (SPARK-13097) Extend Binarizer to allow Double
AND Vector inputs
[ https://issues.apache.org/jira/browse/SPARK-13097?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiangrui Meng resolved SPARK-13097.
-----------------------------------
Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 10976
[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
> Assignee: Mike Seddon
> Priority: Minor
> Fix For: 2.0.0
>
>
> To enhance the existing SparkML Binarizer [SPARK-5891] to allow Vector in addition to the existing Double input column type.
> https://github.com/apache/spark/pull/10976
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org