Dear useRs,
an update of the ROCR package is available on CRAN.
ROCR helps in evaluating the performance of scoring classifiers using
ROC graphs, precision/recall plots, lift charts and many other
performance metrics.
For further information check http://rocr.bioinf.mpi-sb.mpg.de and
http://bioinformatics.oxfordjournals.org/cgi/reprint/21/20/3940
NEWS:
- added an optional parameter 'fpr.stop' to the performance measure
'auc',
allowing to calculate the partial area under the ROC curve
up to the false positive rate given by 'fpr.stop'.
- fixed bug in 'prediction' function which caused ROCR to halt
in the context of a custom label.ordering (thanks to Roberto Perdisci
for pointing out)
As usual, any feedback is more than welcome!
- Tobias
--
Tobias Sing
Computational Biology and Applied Algorithmics
Max Planck Institute for Informatics
Saarbrucken, Germany
Phone: +49 681 9325 315
Fax: +49 681 9325 399
http://www.tobiassing.net
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