Package: ROCR
Title: Visualizing the performance of scoring classifiers.
Version: 1.0-1
Date: 2005-02-23
Depends: gplots
Author: Tobias Sing, Oliver Sander, Niko Beerenwinkel, Thomas Lengauer
Description: ROC 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.
Maintainer: Tobias Sing <tobias.sing@mpi-sb.mpg.de>
License: GPL (version 2 or later)
URL: http://rocr.bioinf.mpi-sb.mpg.de/
Packaged: Sat Feb 26 03:50:29 2005; root
Built: R 2.1.1; ; 2005-07-13 11:00:03; unix
