MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company notices that the prediction distribution of their deployed model has shifted significantly from the training data distribution, but the input data distribution remains unchanged. Which type of drift is occurring, and what is the MOST likely cause?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Concept drift; the underlying relationship between features and target has changed
Concept drift occurs when the relationship between input features and target variable changes, causing prediction distribution shift. Data drift would be input distribution change. The scenario specifically says input distribution unchanged but predictions shifted, indicating concept drift. Possible cause: change in customer behavior or market conditions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Data drift; the training data is no longer representative of the current environment
Why it's wrong here
Data drift refers to input distribution change, which is not happening here.
- ✗
Bias drift; the model is making unfair predictions against a protected group
Why it's wrong here
Bias drift relates to fairness metrics, not overall prediction distribution.
- ✓
Concept drift; the underlying relationship between features and target has changed
Why this is correct
Concept drift changes the prediction function while input distribution remains stable.
- ✗
Model drift; the model has degraded due to software issues
Why it's wrong here
Model drift is a general term, not specific to prediction distribution shift with unchanged inputs.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.