THE RESULT
What the data shows
The largest computed metric is 0.8175 for poutcome; the smallest is 0 for marital. Metric: unknown_share (Unknown share).
A documented unknown category is not the same as an empty CSV cell. Coverage differences may reflect workflow selection.
| field | unknown rows | unknown share | unknown response | known response |
|---|---|---|---|---|
| job | 288 | 0.00637 | 0.1181 | 0.117 |
| marital | 0 | 0 | Unavailable | 0.117 |
| education | 1,857 | 0.04107 | 0.1357 | 0.1162 |
| contact | 13,020 | 0.288 | 0.04071 | 0.1478 |
| poutcome | 36,959 | 0.8175 | 0.09162 | 0.2306 |
THE METHOD
From source to answer
Field-level missing-category coverage and observed outcome comparison.
The Python source exposes this study’s transformations. The complete project download includes shared preparation and evaluation routines.
THE NEXT DECISION
What follows from the finding
Improve source capture for fields with material unknown coverage, then reassess model stability.
Where the conclusion stops
Observational marketing records do not identify campaign uplift. Month and row order are not precise timestamps; repeated-client identifiers are unavailable. Models are research diagnostics, not financial eligibility or automated contact decisions.
Related studies may reuse observations or holdouts. These are historical analyses; associations and backtests do not demonstrate commercial impact. Further model tuning needs new, untouched evaluation data.