Is KNN an example of supervised or unsupervised learning?

Is KNN an example of supervised or unsupervised learning?

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

Answer: (B)

KNN is a supervised learning method. It makes predictions by using labeled training examples: to classify a new item, it finds the k closest labeled points and uses their labels (majority vote for classification, average for regression). This relies on having target labels during the learning and prediction process, which is the hallmark of supervised learning. In unsupervised learning, there are no labels to predict, so methods aim to discover structure or patterns rather than map inputs to known outputs. Reinforcement learning centers on learning a policy through rewards in an environment, not on predicting labels from labeled data. Semi-supervised learning uses a mix of labeled and unlabeled data, but the standard KNN approach uses labels directly to assign the new instance, making it a supervised technique.

KNN is a supervised learning method. It makes predictions by using labeled training examples: to classify a new item, it finds the k closest labeled points and uses their labels (majority vote for classification, average for regression). This relies on having target labels during the learning and prediction process, which is the hallmark of supervised learning. In unsupervised learning, there are no labels to predict, so methods aim to discover structure or patterns rather than map inputs to known outputs. Reinforcement learning centers on learning a policy through rewards in an environment, not on predicting labels from labeled data. Semi-supervised learning uses a mix of labeled and unlabeled data, but the standard KNN approach uses labels directly to assign the new instance, making it a supervised technique.