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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-26721) Bug in feature importance calculation in GBM (and possibly other decision tree classifiers)
Date Wed, 13 Feb 2019 14:15:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-26721?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-26721:
------------------------------------

    Assignee:     (was: Apache Spark)

> Bug in feature importance calculation in GBM (and possibly other decision tree classifiers)
> -------------------------------------------------------------------------------------------
>
>                 Key: SPARK-26721
>                 URL: https://issues.apache.org/jira/browse/SPARK-26721
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 2.4.0
>            Reporter: Daniel Jumper
>            Priority: Major
>
> The feature importance calculation in org.apache.spark.ml.classification.GBTClassificationModel.featureImportances
follows a flawed implementation from scikit-learn resulting in incorrect importance values.
This error was recently discovered and updated in scikit-learn version 0.20.0. This error is
inherited in the spark implementation and needs to be fixed here as well.
> As described in the scikit-learn release notes ([https://scikit-learn.org/stable/whats_new.html#version-0-20-0]):
> {quote}Fix Fixed a bug in ensemble.GradientBoostingRegressor and ensemble.GradientBoostingClassifier
to have feature importances summed and then normalized, rather than normalizing on a per-tree
basis. The previous behavior over-weighted the Gini importance of features that appear in
later stages. This issue only affected feature importances. #11176 by Gil Forsyth.
> {quote}
> Full discussion of this error and debate ultimately validating the correctness of the
change can be found in the comment thread of the scikit-learn pull request: [https://github.com/scikit-learn/scikit-learn/pull/11176] 
>  
> I believe the main change required would be to the featureImportances function in mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala
, however, I do not have the experience to make this change myself.



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