Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

IAPP Exam AIGP Topic 2 Question 23 Discussion

Actual exam question for IAPP's AIGP exam
Question #: 23
Topic #: 2
[All AIGP Questions]

What is the technique to remove the effects of improperly used data from an ML system?

Show Suggested Answer Hide Answer
Suggested Answer: D

Model disgorgement is the technique used to remove the effects of improperly used data from an ML system. This process involves retraining or adjusting the model to eliminate any biases or inaccuracies introduced by the inappropriate data. It ensures that the model's outputs are not influenced by data that was not meant to be used or was used incorrectly. Reference: AIGP Body of Knowledge on Data Management and Model Integrity.


by Alex at Feb 09, 2025, 08:51 AM

Limited Time Offer

25%

Off

Get Premium AIGP Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel
Ettie
5 days ago
Model inversion? Sounds like a magic trick, not a real solution.
upvoted 0 times
...
Eugene
13 days ago
I believe data de-duplication can also help in removing the effects of improperly used data.
upvoted 0 times
...
Stephanie
15 days ago
I agree with Gerald, data cleansing is important to remove improperly used data.
upvoted 0 times
...
Mona
16 days ago
Data cleansing, of course! Who wants their ML system to be bogged down with junk data?
upvoted 0 times
...
Gerald
19 days ago
I think the technique is data cleansing.
upvoted 0 times
...

Save Cancel