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Error Analysis Is Not an Automatic Ranking Rule
Error analysis does not give a single fixed formula for choosing the top improvement task. You still need to judge the likely gain from each error category and compare that with the effort required to address it.
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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 does error analysis not directly give you when deciding the next improvement to make?
Error analysis alone can identify the single highest-priority improvement with no further judgment.
Error analysis does not provide a fixed priority rule
Match each review metric to its role in deciding what to fix first.
Prioritize work using error analysis.
Which two factors should be considered in addition to error percentages when choosing what to fix first?
When deciding which error categories to address first, the effort required for each fix should be considered.
Tradeoffs in Choosing Which Problems to Fix First
Match each description to the role it plays in deciding which error to fix first.
Order the steps for deciding whether one error category should be prioritized first.
Why Error Percentages Alone Do Not Determine Task Priority
Choosing between two fixes after review of failure patterns.
Other factors in choosing which error type to fix first