Computes Kendall's coefficient of concordance
Project description
kendall-w
Author: Ugo Loobuyck
Overview
Computes Kendall's coefficient of concordance for inter-annotator agreement in the case of item ranking between more than two annotators.
Installation
To install use pip:
$ pip install kendall-w
Or clone the repo:
$ git clone https://github.com/ugolbck/kendall-w.git
$ python setup.py install
Usage
import kendall_w as kw
annotations = [
[1, 1, 1, 2],
[2, 2, 2, 3],
[3, 3, 3, 1],
]
W = kw.compute_w(annotations) # returns 0.4375 (fair overall agreement)
Contributions
All contributions are welcome.
How to help?
- Fork this repository to your GitHub account
- Clone the forked repositery to local
- Code something and push to your branch
- Create a pull request from your repository
TODO:
- Handle
pandas.DataFrame
as an input with the instructions in the main file - Write unit tests for compute_w function
- Write code and unit tests for Kendall's tau function ?
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