Human Intuition Can Guide Error Analysis
When an algorithm is worse than humans on a task, error analysis can use human intuition to understand what information a person used to get the right answer and then use that knowledge to modify the learning algorithm. In medical imaging, discussing images with doctors can similarly expose useful intuitions.
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When is human-intuition-guided error analysis most applicable in ML development?
The goal of drawing on human intuition in error analysis is to understand what information a person uses to get the correct answer.
In the speech recognition example, the algorithm incorrectly transcribed 'pair of apples' as '_____ of apples.'
Match each element of human-intuition-guided error analysis to its role in the process.
Order the steps for conducting human-intuition-guided error analysis on an underperforming algorithm.
In medical imaging, how does Machine Learning Yearning recommend drawing on human intuition during error analysis?
Human-intuition error analysis is equally useful whether the algorithm outperforms or underperforms humans.
In Machine Learning Yearning, drawing on human _____ during error analysis helps identify what information leads to the correct answer.
Match each domain or scenario to the correct description of how human intuition is applied in error analysis.
Order the steps a team follows when using doctor intuitions to improve a medical imaging algorithm.