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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #133
You recently built the first version of an image segmentation model for a self-driving car. After deploying the model, you observe a decrease in the area under the curve (AUC) metric. When analyzing t
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Submitted by anna_se· Apr 18, 2026ML model development
Question
You recently built the first version of an image segmentation model for a self-driving car. After deploying the model, you observe a decrease in the area under the curve (AUC) metric. When analyzing the video recordings, you also discover that the model fails in highly congested traffic but works as expected when there is less traffic. What is the most likely reason for this result?
Options
- AThe model is overfitting in areas with less traffic and underfitting in areas with more traffic.
- BAUC is not the correct metric to evaluate this classification model.
- CToo much data representing congested areas was used for model training.
- DGradients become small and vanish while backpropagating from the output to input nodes.
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Topics
#Overfitting#Underfitting#Model generalization#Model evaluation