You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2019/08/06 20:14:00 UTC
[jira] [Updated] (SPARK-28514) Remove the redundant transformImpl
method in RF & GBT
[ https://issues.apache.org/jira/browse/SPARK-28514?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen updated SPARK-28514:
------------------------------
Description:
In GBTClassifier & RandomForestClassifier, the real transform methods inherit from ProbabilisticClassificationModel which can deal with multi output columns.
The transformImpl method, which deals with only one column - predictionCol, completely does nothing. This is quite confusing.
was:
1, In GBTClassifier & RandomForestClassifier, the real transform methods inherit from ProbabilisticClassificationModel which can deal with multi output columns.
The transformImpl method, which deals with only one column - predictionCol, completely does nothing. This is quite confusing.
2, In GBTRegressor & RandomForestRegressor, the transformImpl do exactly what the superclass PredictionModel does (except model broadcasting), so can be removed.
> Remove the redundant transformImpl method in RF & GBT
> -----------------------------------------------------
>
> Key: SPARK-28514
> URL: https://issues.apache.org/jira/browse/SPARK-28514
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 3.0.0
> Reporter: zhengruifeng
> Priority: Minor
>
> In GBTClassifier & RandomForestClassifier, the real transform methods inherit from ProbabilisticClassificationModel which can deal with multi output columns.
> The transformImpl method, which deals with only one column - predictionCol, completely does nothing. This is quite confusing.
>
>
--
This message was sent by Atlassian JIRA
(v7.6.14#76016)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org