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https://issues.apache.org/jira/browse/SPARK-3568?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-3568:
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Priority: Major (was: Minor)
Target Version/s: 1.2.0
Shepherd: Xiangrui Meng
> Add metrics for ranking algorithms
> ----------------------------------
>
> Key: SPARK-3568
> URL: https://issues.apache.org/jira/browse/SPARK-3568
> Project: Spark
> Issue Type: New Feature
> Components: ML, MLlib
> Reporter: Shuo Xiang
> Assignee: Shuo Xiang
>
> Include widely-used metrics for ranking algorithms, including:
> - Mean Average Precision
> - Precision@n: top-n precision
> - Discounted cumulative gain (DCG) and NDCG
> This implementation attempts to create a new class called *RankingMetrics*
> under *org.apache.spark.mllib.evaluation*, which accepts input (prediction
> and label pairs) as *RDD[Array[Double], Array[Double]]*. The following
> methods will be implemented:
> - *averagePrecision(position: Int): Double* this is the presicion@position
> - *meanAveragePrecision*: the average of precision@n for all values of n
> - *ndcg*
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