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| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| data_mining:error_analysis [2018/05/21 22:08] – [Problems with different train and dev/test set dist] phreazer | data_mining:error_analysis [2018/05/21 22:24] (current) – [Problems with different train and dev/test set dist] phreazer | ||
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| If Train and Train-dev would be closer => data-mismatch problem. | If Train and Train-dev would be closer => data-mismatch problem. | ||
| + | Summary: | ||
| + | * Human level 4% | ||
| + | * Avoidable bias | ||
| + | * Train 7% | ||
| + | * Variance | ||
| + | * Train-dev: 10% | ||
| + | * Data mismatch | ||
| + | * Dev: 12% | ||
| + | * Degree of overfitting to dev set (if to high => bigger dev set) | ||
| + | * Test: 12% | ||
| + | |||
| + | ====== Data mismatch problems ====== | ||
| + | |||
| + | * Error analysis to understand difference between training and dev/test set | ||
| + | * Make training more similar / collect more data similar to dev/test set (e.g. simulate audio environment) | ||
| + | * Artificial data synthesis | ||
| + | * Problems: Possible that sampling from too few data (for human it might appear ok) | ||