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I want to use libact for named entity recognition with a probabilistic model. So from my model, I get a score for each token in a sentence how confident it is with the prediction. Can I use libact for my use case? I could not find a clear answer to my problem from the documentation. I don't know if I have to use a scikit-learn learn model or if libact can be used with any kind of probabilistic models.
From my understanding, a query strategy only needs the predictions or the confidence scores from a model for a specific dataset. So theoretically I should be able to plug your implementation of a query strategy into my model to do Active Learning. Does libact support that?
If yes, does an implementation exist of it? The examples I found, only use scikit-learn models.
Thank you for you help!
The text was updated successfully, but these errors were encountered:
You can implement your model by inherit the libact.base.interfaces.ProbabilisticModel and implement its methods.
You can take the example of logistic_regression here:
Then you can pass in your implemented probabilistic model into the query_strategy (active learning algorithm implemented in libact) like other libact models.
Let me know if this solves your question.
Hello guys,
I want to use libact for named entity recognition with a probabilistic model. So from my model, I get a score for each token in a sentence how confident it is with the prediction. Can I use libact for my use case? I could not find a clear answer to my problem from the documentation. I don't know if I have to use a scikit-learn learn model or if libact can be used with any kind of probabilistic models.
From my understanding, a query strategy only needs the predictions or the confidence scores from a model for a specific dataset. So theoretically I should be able to plug your implementation of a query strategy into my model to do Active Learning. Does libact support that?
If yes, does an implementation exist of it? The examples I found, only use scikit-learn models.
Thank you for you help!
The text was updated successfully, but these errors were encountered: