================ The CROC Package ================ A package for calculating ROC curves and Concentrated ROC (CROC) curves written by `Dr. S. Joshua Swamidass `_. Citation -------- Please cite this paper when reporting any work which uses this software: | **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 `_ Description ----------- 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: #. compute the coordinates of both Accumulation Curves and ROC curves. #. handle ties appropriately using several methods. #. compute the BEDROC metric. #. vertically add and average the performance curves of several cross-validation folds. #. focus on the early part of the ROC curve by using several x-axis transforms. Documentation ------------- The docstrings in this module are fairly complete and the scripts provide simple access to the most common functions. Further documentation can be found here: .. toctree:: :maxdepth: 2 install scripts formats r api R-Interface ----------- Daniel Himmelstein has written up a basic R interface to CROC which is avialable on github (`here `_). Development Status ------------------- On 3/14/2010 this project officially moved out of beta and is now designated a stable release. Please email the author_ if you discover any bugs. Future versions will include several enhancements, including: #. the significance tests described in paper. #. better performance and removal of dependence on Sympy. The priority of these improvements will be, in part, directed by interest from users. .. _author : http://swami.wustl.edu/