To perform deeper error analysis on a pipeline component, you must always collect a brand-new set of labeled examples separate from those found during attribution.
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What key opportunity does component attribution create beyond identifying which component caused the most errors?
Examples identified during component attribution can be reused to perform deeper error analysis on that specific component.
After component attribution, the _____ of examples attributed to one component can be reused for a deeper level of error analysis.
Match each pipeline error-analysis concept to its correct description.
Order the steps for leveraging component attribution results to perform deeper error analysis on a specific pipeline component.
In Ng's cat-detection pipeline example, why are the 90 incorrect-bounding-box examples described as 'conveniently found'?
To perform deeper error analysis on a pipeline component, you must always collect a brand-new set of labeled examples separate from those found during attribution.
Ng recommends using the component-attributed examples to carry out a deeper level of _____ on the failing component.
Match each stage of the two-level pipeline error investigation to its primary purpose.
Order the reasoning steps that justify reusing component-attributed examples for deeper analysis rather than collecting new data.
How does component attribution facilitate a secondary layer of error analysis within a machine learning pipeline?
What should you do with the 90 incorrect bounding box examples to improve the cat detector component?
Why are error examples isolated during component attribution valuable for subsequent analysis?