spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-21729) Generic test for ProbabilisticClassifier to ensure consistent output columns
Date Mon, 28 Aug 2017 06:32:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-21729?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16143420#comment-16143420
] 

Apache Spark commented on SPARK-21729:
--------------------------------------

User 'WeichenXu123' has created a pull request for this issue:
https://github.com/apache/spark/pull/19065

> Generic test for ProbabilisticClassifier to ensure consistent output columns
> ----------------------------------------------------------------------------
>
>                 Key: SPARK-21729
>                 URL: https://issues.apache.org/jira/browse/SPARK-21729
>             Project: Spark
>          Issue Type: Test
>          Components: ML
>    Affects Versions: 2.2.0
>            Reporter: Joseph K. Bradley
>
> One challenge with the ProbabilisticClassifier abstraction is that it introduces different
code paths for predictions depending on which output columns are turned on or off: probability,
rawPrediction, prediction.  We ran into a bug in MLOR with this.
> This task is for adding a generic test usable in all test suites for ProbabilisticClassifier
types which does the following:
> * Take a dataset + Estimator
> * Fit the Estimator
> * Test prediction using the model with all combinations of output columns turned on/off.
> * Make sure the output column values match, presumably by comparing vs. the case with
all 3 output columns turned on
> CC [~WeichenXu123] since this came up in https://github.com/apache/spark/pull/17373



--
This message was sent by Atlassian JIRA
(v6.4.14#64029)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message