%0 Journal Article %1 saito2015precision %A Saito, Takaya %A Rehmsmeier, Marc %D 2015 %I Public Library of Science San Francisco, CA USA %J PloS one %K class,imbalance,imbalanced,evaluation,ml,machine,learning,auc,roc,precision,recall,curve citedby:scholar:count:3373 citedby:scholar:timestamp:2024-2-20 %N 3 %P e0118432 %T The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets %V 10

@article{saito2015precision, added-at = {2024-02-20T11:29:31.000+0100}, author = {Saito, Takaya and Rehmsmeier, Marc}, biburl = {https://www.bibsonomy.org/bibtex/25cb3d03e7bfb8faa244b7776947733fc/becker}, interhash = {143b79f7511f261c5f73b718fa20f32d}, intrahash = {5cb3d03e7bfb8faa244b7776947733fc}, journal = {PloS one}, keywords = {class,imbalance,imbalanced,evaluation,ml,machine,learning,auc,roc,precision,recall,curve citedby:scholar:count:3373 citedby:scholar:timestamp:2024-2-20}, number = 3, pages = {e0118432}, publisher = {Public Library of Science San Francisco, CA USA}, timestamp = {2024-02-20T11:29:31.000+0100}, title = {The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets}, volume = 10, year = 2015 }