The automation before I came consist on reading a PDF and extracting values using Machine Learning Skills. Then sending to action center so users can approve them or edit them.
But there are too many fields and now I need to hide or delete some of those fields.
How can I hide/delete now this extra fields so when it is passed to action center, it is cleaner?
Solution
Open and save the data extraction scope window
*I want to delete yellow fields and leave green ones
I believe you have option to show all fields only as of now…unless the field is removed directly from extraction i dont think youc an restrict the display
Can look at this
Cheers
Hi @JavRR ,
Could you let us know why do you want to specifically leave out those fields ?
The automation was done before I came.
And as an enhancement for the project, they have asked me to hide/delete those fields, because no one uses them
I tried just deleting those fields on the taxonomy, but when it came to the extracting activity, when using the ML Skill, it failed.
Saying that those fields were missing.
Yes, I need them to disapear, and users will be thankful. They will get used with a cleaner action center
If you dont need those fields at all…then even in the ml you have to retrain in the datataet where you can delete the fields that are not needed…
So this need to be done both in taxonomy and the ml data labeling as well
Cheers
Damn, I am afraid to edit the whole dataset and labeling because it consists of more than 2,000 pages for training 
But if there is no other way…
You need not redo anything…
Just go to data labelling and delete the non required ones and retrain the model and upgrade the ml skill
There is no re labelling and all involved as already labelling is done…
Cheers
I have hidden those fields because it said:
"Hide fileds when exporting data set)
Now waiting to export and retrain it. Hope it works.
Thank for the suggestion!!
@JavRR ,
It doesn’t necessarily have to be deleted from the labelling and you would not have to re-do the work by labelling or re-training the model (if the model does give out results properly for the other fields which are required accurately).
You would just have to Delete/Remove the fields in the Taxonomy and that would make also the other parts (Data Extraction Scope) to get updated. But if you are receiving errors elsewhere it would mean the value/Key is being used in further checks. You would need to modify the code to adjust to the fields which are required.
If you could provide us with screenshot of the Activities where the errors take place, we can take a further look on what needs to be done.
And also when you removed reom
Taxonomy …I hope you also unlinked the values in the data extraction acope …
Cheers
actually, when I edited the taxonomy and deleted the fields. They appear no more on the extraction scope (exactly the step it was failing), but good to make sure.
Now waiting 36 hours to finish the training. Last pipeline took that time.
I’ll let you know about my results. Thanks again
this
Those are the the values I deleted
@JavRR ,
I did run a test myself using DU template. I did also encountered the same kind of error, in my case there were two, as Train Extractors module had the Train Extractor Scope, where we had to check the Configuration of it as well.
But when corrected and checked the second time, the DU process did work and there weren’t any errors thrown again.
When Checking the Extraction Scope/Train Extractor Scope, make sure that you click on Save and not Cancel, after confirming the fields are deleted.
Let us know if you’re still facing issues.
Hi. This is the solution.
I tested the same. Even the window has less fields, you should click save, as you said.
This solved my issue.
Thanks!
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