Is boosting an example of supervised or unsupervised learning?

Is boosting an example of supervised or unsupervised learning?

• A. Unsupervised
• B. Reinforcement
• C. Semi-supervised
• D. Supervised

Answer: (D)

Boosting is a supervised learning approach. It trains a sequence of simple models, or weak learners, on labeled data, using the mistakes of earlier models to focus the next one on harder examples. Because each training example comes with a known target label, the learning signal comes from comparing predictions to those true labels. This is different from unsupervised learning, which finds structure without labels, and from reinforcement learning, which learns through interaction with an environment and rewards. While boosting can be extended to semi-supervised settings in some cases, the standard, core boosting methods rely on labeled data, making supervised the best description.

Boosting is a supervised learning approach. It trains a sequence of simple models, or weak learners, on labeled data, using the mistakes of earlier models to focus the next one on harder examples. Because each training example comes with a known target label, the learning signal comes from comparing predictions to those true labels. This is different from unsupervised learning, which finds structure without labels, and from reinforcement learning, which learns through interaction with an environment and rewards. While boosting can be extended to semi-supervised settings in some cases, the standard, core boosting methods rely on labeled data, making supervised the best description.