Timeline for What approach should I take for my product classification ML model with user feedback for improving result accuracy?
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 7, 2021 at 7:34 | vote | accept | Julian Gherghel | ||
| Oct 6, 2021 at 15:02 | comment | added | German C M | please do not forget to validate the answer if you are happy with it ;) | |
| Oct 6, 2021 at 14:38 | comment | added | Julian Gherghel | That's spot on! Thanks for the clarification | |
| Oct 6, 2021 at 14:19 | comment | added | German C M | if I understood your use case, you want to provide a level of confidence to the end user for selecting the right category based on the entered name and description (so, this is the model inference); once the user selects the category (the actual one), this means a new entry for your history training set, used in a next model training phase | |
| Oct 6, 2021 at 14:01 | comment | added | Julian Gherghel | Thanks for that! Would this approach enable user input which then gets fed back into the model to help improve model performance over time? This is a user requirement. | |
| Oct 6, 2021 at 13:56 | history | answered | German C M | CC BY-SA 4.0 |