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Which of the following could be used to BEST identify underlying patterns in control effectiveness within unlabeled data elements?
Suggested Answer: C
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When data is 'unlabeled' (meaning the outcomes or 'answers' are not provided), supervised methods like Random Forest (Option D) or XGBoost (Option A) cannot be used. 'Unsupervised learning' is specifically designed to discover 'underlying patterns,' clusters, or latent structures in data without human guidance. For an auditor, unsupervised techniques (like clustering) are invaluable for exploratory analysis, such as grouping similar control failures or identifying unusual transactional behaviors that have not yet been categorized as fraudulent or legitimate.
15 comments · newest first
CA
Carlene
1 month ago
B) Reinforcement learning is more about decision-making, not patterns.
GW
Gwen
1 month ago
C) Unsupervised learning can reveal hidden structures.
VI
Vilma
1 month ago
D) Random forest is great too, but still requires some labeled data.
AN
Antonio
2 months ago
A) XGBoost learning is powerful, but it needs labels.
HU
Hui
2 months ago
Agreed! Unsupervised learning finds patterns without labels.
RE
Rebeca
2 months ago
I think C) Unsupervised learning is the best choice. It’s designed for unlabeled data.
CR
Cristy
2 months ago
Not sure about unsupervised learning being the best option here...
RE
Reita
2 months ago
Wait, can reinforcement learning even handle unlabeled data?
BA
Barney
2 months ago
XGBoost is great, but it needs labeled data, right?
LA
Lavonda
3 months ago
I think random forest could work too, but not as well.
DA
Dallas
3 months ago
Unsupervised learning is the way to go for unlabeled data!
AR
Arthur
3 months ago
Reinforcement learning seems off-topic for this question; I don't recall it being used for identifying patterns in unlabeled datasets.
CA
Caitlin
3 months ago
Random forest could be useful too, but I feel like it’s more about classification rather than finding patterns in unlabeled data.
HY
Hyman
3 months ago
I remember practicing a question about control effectiveness, and I think XGBoost was mentioned as a strong method, but it might not be the best for unlabeled data.
DW
Dwight
4 months ago
I think unsupervised learning is the right choice here since it deals with unlabeled data, but I'm not completely sure.