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As more articles are gathered, analysed and verified by a human, it would be nice for the ML models to self update. Open to discussion on tools and best practices for this.
The text was updated successfully, but these errors were encountered:
The ML I'm thinking of for this particular issue are to tag the articles as about displacement/not about displacement and then as disaster/conflict/other as the reason for displacement
I have an extensive online learning background. Would be interested in details of the problem. Sounds like it may be better to just retrain periodically because this sounds like a supervised learning problem, but it depends on more specifics.
Agreed @oskarsinger. Details pending, of course, but I imagine it may be useful to investigate and then set a threshold for the number of new articles tagged to trigger a retraining.
As more articles are gathered, analysed and verified by a human, it would be nice for the ML models to self update. Open to discussion on tools and best practices for this.
The text was updated successfully, but these errors were encountered: