[jira] [Commented] (SPARK-15041) adding mode strategy for ml.feature.Imputer for categorical features
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https://issues.apache.org/jira/browse/SPARK-15041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17854661#comment-17854661
]
Chhavi Bansal commented on SPARK-15041:
---
Are there plans to have imputations for Categorical string type columns? What
is the recommended way to handle such scenarios?
> adding mode strategy for ml.feature.Imputer for categorical features
>
>
> Key: SPARK-15041
> URL: https://issues.apache.org/jira/browse/SPARK-15041
> Project: Spark
> Issue Type: New Feature
> Components: ML
>Reporter: yuhao yang
>Priority: Minor
> Labels: bulk-closed
>
> Adding mode strategy for ml.feature.Imputer for categorical features. This
> need to wait until PR for SPARK-13568 gets merged.
> https://github.com/apache/spark/pull/11601
> From comments of jkbradley and Nick Pentreath in the PR
> {quote}
> Investigate efficiency of approaches using DataFrame/Dataset and/or approx
> approaches such as frequentItems or Count-Min Sketch (will require an update
> to CMS to return "heavy-hitters").
> investigate if we can use metadata to only allow mode for categorical
> features (or perhaps as an easier alternative, allow mode for only Int/Long
> columns)
> {quote}
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[jira] [Commented] (SPARK-15041) adding mode strategy for ml.feature.Imputer for categorical features
[
https://issues.apache.org/jira/browse/SPARK-15041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16616243#comment-16616243
]
Manu Zhang commented on SPARK-15041:
Is there a plan to add such strategies as min/max ?
> adding mode strategy for ml.feature.Imputer for categorical features
>
>
> Key: SPARK-15041
> URL: https://issues.apache.org/jira/browse/SPARK-15041
> Project: Spark
> Issue Type: New Feature
> Components: ML
>Reporter: yuhao yang
>Priority: Minor
>
> Adding mode strategy for ml.feature.Imputer for categorical features. This
> need to wait until PR for SPARK-13568 gets merged.
> https://github.com/apache/spark/pull/11601
> From comments of jkbradley and Nick Pentreath in the PR
> {quote}
> Investigate efficiency of approaches using DataFrame/Dataset and/or approx
> approaches such as frequentItems or Count-Min Sketch (will require an update
> to CMS to return "heavy-hitters").
> investigate if we can use metadata to only allow mode for categorical
> features (or perhaps as an easier alternative, allow mode for only Int/Long
> columns)
> {quote}
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[jira] [Commented] (SPARK-15041) adding mode strategy for ml.feature.Imputer for categorical features
[
https://issues.apache.org/jira/browse/SPARK-15041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15265411#comment-15265411
]
Gayathri Murali commented on SPARK-15041:
-
I can work on this
> adding mode strategy for ml.feature.Imputer for categorical features
>
>
> Key: SPARK-15041
> URL: https://issues.apache.org/jira/browse/SPARK-15041
> Project: Spark
> Issue Type: New Feature
> Components: ML
>Reporter: yuhao yang
>Priority: Minor
>
> Adding mode strategy for ml.feature.Imputer for categorical features. This
> need to wait until PR for SPARK-13568 gets merged.
> https://github.com/apache/spark/pull/11601
> From comments of jkbradley and Nick Pentreath in the PR
> {quote}
> Investigate efficiency of approaches using DataFrame/Dataset and/or approx
> approaches such as frequentItems or Count-Min Sketch (will require an update
> to CMS to return "heavy-hitters").
> investigate if we can use metadata to only allow mode for categorical
> features (or perhaps as an easier alternative, allow mode for only Int/Long
> columns)
> {quote}
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