ROCR

Package: ROCR
Title: Visualizing the Performance of Scoring Classifiers
Version: 1.0-7
Date: 2015-03-26
Depends: gplots, methods
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-parameterized 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 parameterization 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@gmail.com>
License: GPL (>= 2)
URL: http://rocr.bioinf.mpi-sb.mpg.de/
Packaged: 2015-03-26 10:34:10 UTC; singto1
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-03-26 17:12:17

Install log

* installing to library '/home/ddbj/local/lib64/R/library'
* installing *source* package 'ROCR' ...
** package 'ROCR' successfully unpacked and MD5 sums checked
** R
** data
** demo
** inst
** preparing package for lazy loading
Creating a generic function for 'plot' from package 'graphics' in package 'ROCR'
** help
*** installing help indices
  converting help for package 'ROCR'
    finding HTML links ... done
    ROCR.hiv                                html  
    ROCR.simple                             html  
    ROCR.xval                               html  
    performance-class                       html  
    performance                             html  
    plot-methods                            html  
    prediction-class                        html  
    prediction                              html  
** building package indices
** testing if installed package can be loaded
* DONE (ROCR)
Making 'packages.html' ... done