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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2019/02/13 14:15:00 UTC
[jira] [Assigned] (SPARK-26721) Bug in feature importance
calculation in GBM (and possibly other decision tree classifiers)
[ https://issues.apache.org/jira/browse/SPARK-26721?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-26721:
------------------------------------
Assignee: 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
> Assignee: Apache Spark
> 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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