Author: Ugo Loobuyck
Computes Kendall's coefficient of concordance for inter-annotator agreement in the case of item ranking between more than two annotators.
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
import kendall_w.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)
All contributions are welcome.
- 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
- Handle
pandas.DataFrame
as an input with the instructions in the main file - Use numpy for faster computation?