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Posted to issues@spark.apache.org by "Sean R. Owen (Jira)" <ji...@apache.org> on 2022/06/16 13:26:00 UTC
[jira] [Resolved] (SPARK-39446) Add relevance score for nDCG evaluation in MLLIB
[ https://issues.apache.org/jira/browse/SPARK-39446?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean R. Owen resolved SPARK-39446.
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Fix Version/s: 3.4.0
Resolution: Fixed
Issue resolved by pull request 36843
[https://github.com/apache/spark/pull/36843]
> Add relevance score for nDCG evaluation in MLLIB
> ------------------------------------------------
>
> Key: SPARK-39446
> URL: https://issues.apache.org/jira/browse/SPARK-39446
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 3.2.1
> Reporter: Ryosuke Horiuchi
> Priority: Major
> Fix For: 3.4.0
>
>
> The current implementation of ndcgAt function treats relevance score as binary (as written [Document|[https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.mllib.evaluation.RankingMetrics.html#pyspark.mllib.evaluation.RankingMetrics.ndcgAt]|https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.mllib.evaluation.RankingMetrics.html#pyspark.mllib.evaluation.RankingMetrics.ndcgAt]).
> However, it is better to extend this to accept a user-defined relevance score to calculate nDCG more flexibly.
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