What is Ensemble Learning?
Ensemble methods combine multiple machine learning models to produce better predictions than any individual model.
How We Calculate It
The ensemble prediction is a weighted average of all models, where weights are determined by each model's historical accuracy (R² score).
Formula:
Ensemble = Σ (Predictioni × Weighti) / Σ Weighti
Where Weighti = R²i (model accuracy)
Confidence Range
The 95% confidence range shows where we expect the actual price to fall with 95% probability, calculated from the standard deviation of all model predictions.
💡 Pro Tip: Higher accuracy and tighter confidence ranges indicate more reliable predictions.