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A package for calculating ROC curves and Concentrated ROC (CROC) curves.

Project description

A package for calculating ROC curves and Concentrated ROC (CROC) curves written by Dr. S. Joshua Swamidass.


A CROC Stronger than ROC: Measuring, Visualizing, and Optimizing Early Retrieval
S. Joshua Swamidass, Chloe-Agathe Azencott, Kenny Daily and Pierre Baldi
Bioinformatics, April 2010, doi:10.1093/bioinformatics/btq140


This pure-python package is designed to be a standardized implementation of performance curves and metrics for use either in python scripts or through a simple commandline interface. As a standardized implementation its output is robust enough to be using in publishable scientific work.

With this package, one can easily:

  1. Compute the coordinates of both Accumulation Curves and ROC curves.
  2. Handle ties appropriately using several methods.
  3. Compute the BEDROC metric.
  4. Vertically add and average the performance curves of several cross-validation folds.
  5. Focus on the early part of the ROC curve by using several x-axis transforms.

The docstrings in this module are fairly complete and the scripts provide simple access to the most common functions. Further documentation can be found at

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Files for CROC, version 1.1.26
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Filename, size CROC-1.1.26.tar.gz (13.3 kB) File type Source Python version None Upload date Hashes View

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