predict should return label/tag plus confidence value about flair

[alanakbik]

Yes, we agree :) We are currently implementing this and will push soon into release-0.3 branch for testing, and then (hopefully soon) we will release the next version that will contain this feature!

[kilian-gebhardt]

I'd be interested in confidences for the assigned labels in the sequence labeling tasks (and may implement it, if you are not already working on this).
In case of a linear output layer one can apply an additional softmax to obtain a confidence value. In case of a CRF output layer, it seems as if a forward-backward algorithm is required (which is perhaps a bit too costy).

[alanakbik]

Added to release-03 branch - will be part of next release!

[Rajat-Mehta]

In the case of two label classification, can we somehow get the probability of given text document for both classes?

For example, For a given text document D1, I need output like this:
Class 1: probability 0.7
Class 2: probability 0.3
(both probabilities should be summing to 1)
If yes, how to achieve that? It would be really helpful for me.

Thanks in advance,
Rajat

[alanakbik]

There is a PR pending right now that will allow you to do this, see #693. Once its merged you will have this functionality in the master branch and eventually in the next release of Flair.

[haozturk]

Hi guys, in which versions and how can I use this feature?

Thanks :)

[alanakbik]

Hi @haozturk you already can with the current version:

from flair.data import Sentence
from flair.models import SequenceTagger

tagger = SequenceTagger.load('ner')

sentence = Sentence('I live in Berlin')

tagger.predict(sentence)

for entity in sentence.get_spans('ner'):
    print(entity)
    print(entity.tag)
    print(entity.score)