AdaBoost Classifier, Explained: A Visual Guide with Code Examples

AdaBoost is an ensemble learning model that improves prediction accuracy by focusing on previously misclassified instances. It builds a series of weighted decision trees, where each new tree corrects the mistakes of the previous ones, creating a robust model through adaptive learning. Key parameters include the number of trees Show more