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https://issues.apache.org/jira/browse/SPARK-21594?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16109017#comment-16109017
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Joseph Wang commented on SPARK-21594:
-------------------------------------
Hi, I have tested with the Spark2.2.0 prebuilt release.
This is not a personal issue but an existing issue.
Shall I still send the mail to u...@spark.apache.org?
Joseph
On 8/1/17, 9:33 AM, "Sean Owen (JIRA)" <j...@apache.org> wrote:
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https://issues.apache.org/jira/browse/SPARK-21594?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-21594.
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Resolution: Invalid
This should go to u...@spark.apache.org
> Probability output from MutilayerPerceptronClassifier
> -----------------------------------------------------
>
> Key: SPARK-21594
> URL: https://issues.apache.org/jira/browse/SPARK-21594
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Affects Versions: 2.2.0
> Environment: SPARK, PySpark,Scala, SparkR
> Reporter: Joseph Wang
>
> My question is, is it possible to get not only the labels, but also (or
only) the probability for that label? Like not just 0 or 1 for every input, but
something like 0.95 for 0 and 0.05 for 1. If this is not possible with MLP, but
is possible with other classifier. I have only used MLP because I know they
should be capable of returning the probability, but I can't find it in PySpark.
This is an inconsistent offering which needs to be fixed, which is provided by
other algorithms in Spark MLlib with Spark Data Frame but not MLP which is
related to AI stuff.
> thanks
> Joseph
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> Probability output from MutilayerPerceptronClassifier
> -----------------------------------------------------
>
> Key: SPARK-21594
> URL: https://issues.apache.org/jira/browse/SPARK-21594
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Affects Versions: 2.2.0
> Environment: SPARK, PySpark,Scala, SparkR
> Reporter: Joseph Wang
>
> My question is, is it possible to get not only the labels, but also (or only)
> the probability for that label? Like not just 0 or 1 for every input, but
> something like 0.95 for 0 and 0.05 for 1. If this is not possible with MLP,
> but is possible with other classifier. I have only used MLP because I know
> they should be capable of returning the probability, but I can't find it in
> PySpark. This is an inconsistent offering which needs to be fixed, which is
> provided by other algorithms in Spark MLlib with Spark Data Frame but not MLP
> which is related to AI stuff.
> thanks
> Joseph
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