What is supervised learning in AI?
a) Learning from labeled data
b) Learning without labeled data
c) Learning by trial and error
d) Learning from expert systems
Answer:
a) Learning from labeled data
Explanation:
Supervised learning is a type of machine learning where the model is trained on labeled data. Each input is paired with the correct output, allowing the model to learn the relationship between the two.
The goal of supervised learning is for the model to generalize from the training data and accurately predict the output for new, unseen inputs. Examples of supervised learning algorithms include linear regression, support vector machines, and decision trees.
Supervised learning is commonly used in applications such as image classification, spam detection, and predictive analytics where labeled data is readily available.