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rank_metric: add AUC-PR (#3172)

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* rank_metric: add AUC-PR

Implementation of the AUC-PR calculation for weighted data, proposed by Keilwagen, Grosse and Grau (https://doi.org/10.1371/journal.pone.0092209)

* rank_metric: fix lint warnings

* Implement tests for AUC-PR and fix implementation

* add aucpr to documentation for other languages
This commit is contained in:
Arjan van der Velde
2018-03-23 10:43:47 -04:00
committed by Yuan (Terry) Tang
parent 8fb3388af2
commit 04221a7469
7 changed files with 121 additions and 2 deletions
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R-package/man/xgb.train.Rd
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@@ -186,6 +186,7 @@ The folloiwing is the list of built-in metrics for which Xgboost provides optimi
Different threshold (e.g., 0.) could be specified as "error@0."
\item \code{merror} Multiclass classification error rate. It is calculated as \code{(# wrong cases) / (# all cases)}.
\item \code{auc} Area under the curve. \url{http://en.wikipedia.org/wiki/Receiver_operating_characteristic#'Area_under_curve} for ranking evaluation.
\item \code{aucpr} Area under the PR curve. \url{https://en.wikipedia.org/wiki/Precision_and_recall} for ranking evaluation.
\item \code{ndcg} Normalized Discounted Cumulative Gain (for ranking task). \url{http://en.wikipedia.org/wiki/NDCG}
}