sandy4321 / forest-confidence-interval

Confidence intervals for scikit-learn forest algorithms

forest-confidence-interval: Confidence intervals for Forest algorithms

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

Compatible with Python2.7 and Python3.5

This module is based on R code from Stefan Wager (see important links below) and is licensed under the MIT open source license (see LICENSE)

Important Links

scikit-learn - http://scikit-learn.org/

Stefan Wager's randomForestCI - https://github.com/swager/randomForestCI

Installation and Usage

Before installing the module you will need numpy, scipy and scikit-learn.

pip install numpy scipy scikit-learn

To install the module execute:

pip install forestci

or, if you are installing from the source code:

$ python setup.py install

Examples

See examples gallery