Question

What is the difference between supervised learning and unsupervised learning? Give concrete examples

Answer 1

Supervised learning involves learning a function that maps an input to an output based on example input-output pairs [1].

For example, if I had a dataset with two variables, age (input) and height (output), I could implement a supervised learning model to predict the height of a person based on their age.

Answer 2

Supervised learning is a system in which both input and desired output data are provided. Input and output data are labeled to provide a learning basis for future data processing.

Unsupervised learning procedure does not need labeling information explicitly, and the operations can be carried out without the same. The common unsupervised learning method is cluster analysis. It is used for exploratory data analysis to find hidden patterns or grouping in data.