I have a task to calculate inter-annotator agreement in multi-label classification, where for each example more than one label can be assigned. I found that NLTK can measure agreement based on a distance metric.
I am looking for an example of calculating krippendorff alpha with MASI distance.
This is what I have.
import nltk
from nltk.metrics import masi_distance
toy_data = [['1', 5723, [1,2]],['2', 5723, [2,3]]]
task = nltk.metrics.agreement.AnnotationTask(data=toy_data, distance=masi_distance)
print task.alpha()
This code fails with
TypeError: unhashable type: 'list'
The following doesn't work either:
toy_data = [['1', 5723, set([1,2])],['2', 5723, set([2,3])]]
Do you have a working example? Thank you!
To be more precise, what needs to be a frozenset (as @alexis has pointed out) is just the third member of the triple, this is the labels assigned to the item.
toy_data = [['1', 5723, frozenset([1,2])],['2', 5723, frozenset([2,3])]]