Metadata-Version: 2.0
Name: forestci
Version: 0.3
Summary: forestci: confidence intervals for scikit-learn forest algorithms
Home-page: http://github.com/scikit-learn-contrib/forest-confidence-interval
Author: Ariel Rokem
Author-email: arokem@uw.edu
License: MIT
Description-Content-Type: UNKNOWN
Platform: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Requires-Dist: nose (>=1.1.2)
Requires-Dist: numpy (>=1.8.2)
Requires-Dist: scikit-learn (>=0.17)



sklearn forest ci
=================

`forest-confidence-interval` is a Python module for calculating variance and
adding confidence intervals to scikit-learn random forest regression or
classification objects. The core functions calculate an in-bag and error bars
for random forest objects

Please read the repository README_ on Github or our documentation_

.. _README: https://github.com/scikit-learn-contrib/forest-confidence-interval/blob/master/README.md

.. _documentation: http://contrib.scikit-learn.org/forest-confidence-interval/



