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Mislabeled Examples in the Dev Set
During error analysis, one may notice that some examples in the dev set are mislabeled. Here, "mislabeled" means that the pictures were already mislabeled by a human labeler before the algorithm encountered them; that is, in an example , the class label has an incorrect value. For example, some pictures that are not cats may be mislabeled as containing a cat, and vice versa.
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What does error analysis primarily examine to understand an ML system's mistakes?
There is exactly one correct method for conducting error analysis on an ML system.
The process of looking at misclassified examples to understand error causes is called _____.
Match each error analysis concept to its correct description from Machine Learning Yearning.
Order the steps of conducting a basic error analysis on a dev set as described in Machine Learning Yearning.
What is the primary goal of reviewing misclassified examples during error analysis, even in categories you cannot yet fix?
Machine Learning Yearning describes error analysis as an iterative process.
Error analysis can often help you figure out how _____ different improvement directions are.
Match each error analysis activity to the benefit it provides according to Machine Learning Yearning.
Order the reasoning steps for deciding which error categories to pursue after completing an initial error analysis.