THE RESULT
What the data shows
The largest computed metric is 13.2 for Median baseline; the smallest is 4.341 for Extra trees. Metric: mae (MPa MAE).
All ages of an identical composition stay in the same split; this prevents repeated-formulation overlap.
| model | mae | rmse | r2 | bias |
|---|---|---|---|---|
| Median baseline | 13.2 | 16.28 | -0.01351 | -1.879 |
| Ridge | 8.001 | 10.07 | 0.6117 | 1.088 |
| Extra trees | 4.341 | 5.671 | 0.877 | 0.421 |
THE METHOD
From source to answer
Grouped composition split, fixed Ridge and Extra Trees benchmarks, original-unit errors.
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: strength
Inputs: cement, slag, fly_ash, water, superplasticizer, coarse_aggregate, fine_aggregate, age
THE NEXT DECISION
What follows from the finding
Assess external laboratory generalization before any engineering application.
Where the conclusion stops
Laboratory observations do not certify a construction mix. Composition and curing conditions are confounded. Models require independent engineering validation and cannot replace strength testing.
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.