Name: Ensemble Methods Lab
Author: MySimulator

Ensemble setup

Number of stumps: 7

Each stump is an axis-aligned threshold rule (like "if x > 0.3, predict class 1") trained on a bootstrap resample of the data — individually weak, but each looks at a different slice of the problem.

Accuracy

Best single stump—

Average single stump—

Ensemble (combined)—

Ensemble decision boundary (background) over training points