Fast, vectorized metrology with binary contingency counts.
Project description
Contingency
Fast, vectorized metrology with binary contingency counts.
Rapidly calculate binary classifier metrics like MCC, F-Scores, and Average Precision Scores from scalar and binary predictions.
For an overview of features, usage, and performance, see the documentation site. The canonical entry for this publication on the NIST data repository is available at doi:10.18434/mds2-4079.
Installation
contingency can be installed from PyPI:
pip install contingency-tools
If you would like access to the most recent/unstable version on GitHub (before a release):
pip install git+https://github.com/usnistgov/Contingency.git
For access to the NIST PDR entry for contingency, see data.nist.gov.
Contact the PI
rachael.sexton@nist.gov- NIST Engineering Laboratory
- Systems Integration Division
- Information Modeling & Testing Group
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