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New Error Categories Can Appear During Review
When you inspect examples the model got wrong, you often notice patterns that were not part of your original checklist. For example, if many failures come from dim indoor photos, you might add a separate "low light" column to your review table. A useful habit is to ask whether a person could have handled the case correctly, since that question can reveal both new error categories and possible fixes.
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One Example May Fit Several Error Tags
New Error Categories Can Appear During Review
Choose Error Categories You Can Act On
Error Review Improves Through Repeated Passes
Using Error Counts to Decide Where to Focus Next
Working on Several Error Buckets at Once
Error Analysis Is Not an Automatic Ranking Rule
A Category's Share of Errors Sets an Upper Bound on Improvement
Error Analysis Helps Estimate Whether a Proposed Change Is Worth the Effort
Why Quick Error Review Is Often Skipped
Incorrect Labels in a Validation Set
Splitting a large development set into a review subset and a tuning subset
Build a Simple Baseline First, Then Use Error Analysis to Prioritize Improvements
Using Training-Set Mistakes to Diagnose High Bias
Reviewing a Sample of Validation Errors
Separating Search Errors from Scoring Errors in Inference
Component-Wise Error Review
Error Analysis as a Data-Science Lens on Model Mistakes
Multiple Valid Approaches to Error Analysis
Tasks Humans Can Perform Give Stronger Error Analysis Benchmarks
When diagnosing a model, what should error analysis focus on first?
Error analysis on a machine learning system must follow one fixed procedure.
Name the practice of reviewing mistakes to understand why predictions failed.
Match each error-analysis idea to the description that best fits it.
Put the steps of a simple dev-set error review in the right order.
Why is it useful to inspect misclassified examples during error analysis, even for error types you cannot immediately repair?
Error analysis is usually repeated after each round of model changes.
Error analysis can help you judge which improvement paths look most _____.
Match each error-analysis activity with the benefit it can provide.
Order the steps for deciding which error types to target after a first pass of error review.
Why Error Review Helps Set the Right Next Priorities
Plan the next review step after repeated image-classifier mistakes.
What is error analysis used for in machine learning?
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What often happens when you inspect misclassified cases during error analysis?
You must finish defining every error category before reviewing any mislabeled examples.
After you discover that many mistakes come from night-time, motion-blurred photos, you should add a new _____ to the error analysis spreadsheet.
Match each review step to its main role in uncovering new error categories.
Order the steps for expanding error categories during review of mistakes.
When examining a misclassified satellite photo, which question is most useful for uncovering new error categories and fixes?
Reviewing a sample of mistakes can uncover a recurring error type that was not included in the original error categories.
Finding New Error Categories
Match each term from an error-review framework to its description.
Put the error-analysis steps in order after you notice a new pattern in reviewed examples.
Why Error Categories Should Keep Evolving
Spotting a New Error Category During Review
A Human-Comparison Question for Error Review