Table 2 Comparison of ensemble methods.
From: Boosting skin cancer diagnosis accuracy with ensemble approach
Method | Strengths | Weaknesses |
|---|---|---|
Max Voting | Simple, leverages diversity | Ignores model performance |
Bagging | Reduces variance, stabilizes models | Requires large datasets, does not reduce bias |
Boosting | Reduces bias, improves accuracy on hard cases | Computationally costly, sensitive to noise |
Stacking | Allows complex combinations | Requires tuning, risk of overfitting |
