Differences
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| Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision | ||
| data_mining:error_analysis [2018/05/21 19:38] – [Working on most promising problems] phreazer | data_mining:error_analysis [2018/05/21 19:46] – [Misslabeled data] phreazer | ||
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| Line 130: | Line 130: | ||
| Result: Calc percentage of problem category (potential improvement " | Result: Calc percentage of problem category (potential improvement " | ||
| + | General rule: Build your first system quickly, then iterate (dev/test setup, build system, bias/ | ||
| ====== Misslabeled data ====== | ====== Misslabeled data ====== | ||
| Line 138: | Line 139: | ||
| Principles when fixing labels: | Principles when fixing labels: | ||
| - | - Apply same process to dev and test set (same distribution) | + | * Apply same process to dev and test set (same distribution) |
| - | - Also see what examples algo got right (not only wrong) | + | |
| - | - Train and dev/test data may come from different distribution (no problem if slightly different) | + | |