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Is there any way to predict a single-label output using multi-label features?

I am now working with a document type prediction model. Each document has at least one label and 7 different labels are used in labelling the data.

Given a series of documents, I am trying to predict the label for the current document based on labels of the previous documents.

I'd say this problem is a multi-class classification with multi-label features as I'm trying to make a machine give only 1 possible label for an unknown input.

I've tried both multi-class and multi-label classification on Scikit Learn. My impression is that we can only perform multi-label classification with multi-labelled data. Are there any Scikit Learn classifiers that can do multi-label --> single label predictions? If not, are there any other ways to do so?

hmsquare
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You should try Simple Transformer Models and I am giving you a link where you explore the different models related to multiclass and multilabel

https://simpletransformers.ai/docs/usage/#configuring-a-simple-transformers-model

Vikas Kumar
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  • Thanks for the suggestion. Still, is it possible to do it on scikit learn? I'm attempting to just take the current and previous labels into consideration and isn't going to introduce NLP stuff into my model yet. – hmsquare Jul 15 '21 at 05:44