THE RESULT
What the data shows
The largest computed metric is 0.5465 for white; the smallest is 0.444 for red. Metric: mae (Sensory-score MAE).
This is a subgroup diagnostic of the shared holdout, not a separate independent validation.
| wine type | test samples | mae | bias |
|---|---|---|---|
| red | 334 | 0.444 | 0.03391 |
| white | 954 | 0.5465 | -0.01428 |
THE METHOD
From source to answer
Held-out residual summaries stratified by wine type for a fixed Extra Trees model.
The Python source exposes this study’s transformations. The complete project download includes shared preparation and evaluation routines.
EVALUATION
How the result was checked
Fixed 80/20 split of unique input groups (seed 42); exact input duplicates stay together.
Fixed configurations specified before scoring; no tuning on the holdout.
Target and input features
Target: quality
Inputs: fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, total_sulfur_dioxide, density, ph, sulphates, alcohol, wine_type
THE NEXT DECISION
What follows from the finding
Investigate subgroup calibration and obtain external batch-level validation before specialization.
Where the conclusion stops
Sensory scores are ordinal and concentrated in the middle. Producer and batch IDs are unavailable. Associations are not recipes for changing quality or evidence of market price.
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.