Fig. 2. Illustration of ensemble learning and adaptive boosting.

a Ensemble learning: L₁, L₂, …, L_n are independent learners trained on the entire training data D. The stacked generalizer is a logistic regression model trained to produce a final prediction P based on the decisions from individual classifiers. Model performance is measured using the final predictions. b Adaptive boosting: checkmarks and crosses indicate correctly and incorrectly classified instances, respectively. The heights of the rectangles are proportional to the weights of the training instances. A sequence of learners, L₁, L₂, …, L_n, is generated with each new model trained on a re-weighted dataset, which boosts the weights of the misclassified training instances in the previous model.