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Error Analysis Helps Estimate Whether a Proposed Change Is Worth the Effort
Before spending substantial engineering time on a possible improvement, error analysis can provide a fast estimate of how much the change might move validation performance. That estimate gives a practical basis for deciding whether the work is likely worth the effort or whether resources should go to a different task.
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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 is the best first step before spending several weeks on a proposed model change?
Error analysis can provide a quantitative basis for deciding whether a proposed improvement is worth the engineering effort.
Before spending two weeks on a feature, the safest first step is to _____ its likely effect on validation accuracy.
Match each error-analysis idea to how it helps with project investment decisions.
Order the steps for using error analysis to decide whether a model improvement is worth funding.
What does an error-counting review help you estimate quickly?
Build first, estimate later
Error analysis provides a fast estimate of the possible _____ gained by adding a new improvement to a machine learning system.
Match each error-analysis finding to the investment decision it most directly supports.
Order the steps for deciding whether fixing one error type deserves a month of engineering work.
Using Error Analysis to Judge Whether an Improvement Is Worth the Effort
Deciding Whether to Add a Commercial OCR Module
Deciding Whether a Planned Improvement Is Worth the Time