Model Insights
What does the model actually use to predict prices, and why did it predict what it did for one specific product?
Model performance
The model was trained on 5.2m data points and tested on a hold-out set of 444.3k records it never saw during training.
Average prediction error
£0.15
On a typical product, the forecast is within this much of the real price (MAE).
Error, penalising big misses
£1.26
Same idea, but weighted so rare large errors count more (RMSE).
Dataset size
9.5m
Total price records analysed.
Loading precomputed SHAP analysis…