GNU R package to prepare and display ROC curves
DescriptionROC graphs, sensitivity/specificity curves, lift charts, and precision/recall plots are popular examples of trade-off visualizations for specific pairs of performance measures. ROCR is a flexible tool for creating cutoff-parametrized 2D performance curves by freely combining two from over 25 performance measures (new performance measures can be added using a standard interface). Curves from different cross-validation or bootstrapping runs can be averaged by different methods, and standard deviations, standard errors or box plots can be used to visualize the variability across the runs. The parametrization can be visualized by printing cutoff values at the corresponding curve positions, or by coloring the curve according to cutoff. All components of a performance plot can be quickly adjusted using a flexible parameter dispatching mechanism. Despite its flexibility, ROCR is easy to use, with only three commands and reasonable default values for all optional parameters. ROCR features: ROC curves, precision/recall plots, lift charts, cost curves, custom curves by freely selecting one performance measure for the x axis and one for the y axis, handling of data from cross-validation or bootstrapping, curve averaging (vertically, horizontally, or by threshold), standard error bars, box plots, curves that are color-coded by cutoff, printing threshold values on the curve, tight integration with Rs plotting facilities (making it easy to adjust plots or to combine multiple plots), fully customizable, easy to use (only 3 commands). Performance measures that ROCR knows: Accuracy, error rate, true positive rate, false positive rate, true negative rate, false negative rate, sensitivity, specificity, recall, positive predictive value, negative predictive value, precision, fallout, miss, phi correlation coefficient, Matthews correlation coefficient, mutual information, chi square statistic, odds ratio, lift value, precision/recall F measure, ROC convex hull, area under the ROC curve, precision/recall break-even point, calibration error, mean cross-entropy, root mean squared error, SAR measure, expected cost, explicit cost.
1910 other people were interested in this package here. The newest known version of this software is 1.0-7-4 (Information last updated about 12 hours ago.)
Upload new screenshots
Thanks for uploading more screenshots. Please note:
- Your screenshot should contain a typical scene when working with it.
- Take only a screenshot of the respective application and not of your whole desktop (unless the screenshot is meant for a window manager).
- Your screenshots must be in PNG format.
- You can upload multiple images at once.
- Your screenshot need to be approved by the moderators first. You will already see your screenshot but it will not be visible to others instantly. If moderators reject your upload you will get notified next time you visit this site (requires cookies).
- Images larger than 800x600 pixels will automatically be reduced. So don't try to capture too much detail in a screenshot. It may become unreadable. Shrink the applications window if possible.
- Screenshots are made public and can freely be used by anyone.
- Useful programs for making screenshots are shutter, ksnapshot (KDE), gimp, xwd or scrot. See the Debian wiki for more information on how to make screenshots under Debian.
- Please set your language to english so that everybody understands it. If you don't use english by default please start your application from a shell using after setting "export LANG=C".