Uses algorithms that input a set of labeled training data to attempt to learn the differences between the given labels. Supervised learning is further divided into two subcategories, namely, classification and regression. Which term describes this approach?

Uses algorithms that input a set of labeled training data to attempt to learn the differences between the given labels. Supervised learning is further divided into two subcategories, namely, classification and regression. Which term describes this approach?

• A. Unsupervised Learning
• B. Regression
• C. Machine Learning
• D. Supervised Learning

Answer: (D)

Learning from labeled data to predict the correct labels is called supervised learning. In this approach, training data come with the answers, so the algorithm learns to map input features to the corresponding labels. After training, it can predict labels for new data. The two subcategories—classification (discrete categories) and regression (continuous values)—are built on this same idea. This distinguishes it from unsupervised learning, which uses only unlabeled data to find structure, and from the broader field of machine learning, which includes both supervised and unsupervised methods.

Learning from labeled data to predict the correct labels is called supervised learning. In this approach, training data come with the answers, so the algorithm learns to map input features to the corresponding labels. After training, it can predict labels for new data. The two subcategories—classification (discrete categories) and regression (continuous values)—are built on this same idea. This distinguishes it from unsupervised learning, which uses only unlabeled data to find structure, and from the broader field of machine learning, which includes both supervised and unsupervised methods.