I have a process that is using the Document Understanding Invoices ML Package to read data from Invoices. We are getting the Invoices sent to Action Center for human validation, and I can export the results of the human input with the Export Extraction Results activity. I also see how the ML Skill Upload File activity works to upload the export data into a dataset to then train from. How do I connect the dots between uploading the dataset with the Upload File activity, then using this in a pipeline run to train the model? Does anyone have an example they can show of this is done? I need the bot to be able to take the results from the human validation in Action Center and include these in the ML model training. Any help is much appreciated!
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Welcome to the community.
Here you can find documentation on how to use Data Extraction Training: https://docs.uipath.com/document-understanding/docs/data-extraction-training-overview
I bit late but maybe I can still help you.
Here’s a new feature currently in public preview which you might want to look into:
Also, I highly recommend using the Document Understanding Process Template, it can already automatically upload your trained documents:
If this has helped you, please mark this answer as the solution.
Have you found the solution to this ? I have the same problem as you
I believe, the training part of packaging has to be done manually for now. So, whenever you get the trained validated set out of the action center, you would require to have those outputs stored in the share drives. where as, you may train the package (retrainable one) once/thrice in a month by manually uploading the dataset in the Ai Center. I dont think there is any approach for the bot to train itself out of application outputs (Atleast for now)