predictive intelligent change capability when train

Cherly
Tera Contributor

After the upgrade to Vancouver. when we train the capability change to from classification to Workflow Classification. is there any way to change fix this issue.

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Brian Bakker
ServiceNow Employee
ServiceNow Employee

@Cherly 

This is not an issue, as you have seamlessly moved to our new ML Trainers that have an improved Classifier engine using a pre-trained Word Corpus that will provide better prediction results. Please check the Solution Statistics and compare it with the solution trained with the "Classification" capability and you will see improved stats (higher % is better).

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19 REPLIES 19

@sakshi arora 

We have documented the new ML APIs with examples in Using Machine Learning APIs

Hi @Brian Bakker ,

Thanks for the previous response. We have now updated our ML solutions to new ML capability of Workflow classification and have got one issue post we updated : previously training schedules were running automatically based on the training frequency being set. But since we have updated the solutions with workflow classification capability, solutions are not getting re-trained on its own. Do we have to do any other specific change to auto train these solutions in the new capability?

@sakshi arora 

Workflow Classification solutions should be no different when it comes to auto-training them. However, we did fix an issue when upgrading to Washington that did cause auto-training of solutions to stop working. In this scenario, you will need to click on the "Update & Train" button, and it will now create a new Training Schedule, and auto-retrain the Workflow Classification solution based on the Training Frequency set in the solution definition. We apologise for the inconvenience caused, but auto-training is the same for both Classification and Workflow Classification solutions.

 

Hope this helps.

 

Regards,

Brian

Seems re-training manually helped resolved the issue. Thankyou!

Have to say that our solution gets the wrong prediction most of the time. Taking a look at the link above but not written well to follow when trying to follow incorrect predictions on almost every test.