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Examples Can Belong to Multiple Error Categories
One example can be associated with multiple categories in an error-analysis spreadsheet. For example, Image #3 has both the Great Cat and Blurry columns checked. Because examples can have multiple categories, the percentages at the bottom may not add up to 100%.
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Examples Can Belong to Multiple Error Categories
Discovering New Error Categories While Reviewing Examples
Most Helpful Error Categories Are Ones You Have Ideas to Improve
Error Analysis Is an Iterative Process
Error Category Frequency Helps Indicate Which Categories to Focus On
Pursuing Multiple Error Categories in Parallel
Error Analysis Does Not Yield a Rigid Priority Formula
Error Category Fraction as a Ceiling on Possible Error Reduction
Error Analysis as a Quantitative Basis for Project Investment Decisions
Engineer Reluctance to Perform Error Analysis Despite Its Low Time Cost
Mislabeled Examples in the Dev Set
Splitting a Large Dev Set into a Manually Examined Subset and a Hands-Off Subset
Build a Basic System Quickly and Iterate Using Error Analysis
Training Set Error Analysis for High Bias
Manually Reviewing 100 Speech Recognition Dev Set Examples
Debugging Inference Algorithms
Error Analysis by Parts
Error Analysis as Data Science for ML Mistakes
No Single Right Way to Perform Error Analysis
Human-Solvable Problems Enable More Powerful Error Analysis Tools
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.
Learn After
Why may the category percentages in an error analysis spreadsheet not add up to 100%?
In an error analysis spreadsheet, each misclassified example must belong to exactly one error category.
Because one misclassified example can be associated with _____ categories, the column percentages in an error analysis spreadsheet may not add up to 100%.
Match each error analysis spreadsheet concept to its correct description.
Order the steps for conducting error analysis on misclassified dev-set examples using a category spreadsheet.
In Machine Learning Yearning, Image #3 has both the 'Great Cat' and 'Blurry' columns checked. What concept does this directly illustrate?
If column percentages in an error analysis spreadsheet sum to more than 100%, it necessarily indicates a data entry mistake was made.
In Machine Learning Yearning's error analysis illustration, Image #3 has both the Great Cat and the _____ columns checked.
Match each observation about an error analysis spreadsheet to the implication it directly supports.
Order the reasoning steps to correctly interpret column percentages that sum to more than 100% in an error analysis spreadsheet.