Question

Compare and contrast supervised and unsupervised learning. Give specific examples to explain both.

Answer 1

Ans) Supervised and Unsupervised learning:

1) Supervised learning with example:

- Supervision refers to the fact that the training dataset that we use to build classification models include that actual class labels of existing observations.

- Goal is to predict the class label of the new data based on the training set.

2) Unsupervised learning (clustering) with example:
- Class labels of training data are either unknown or do not exist at all.

- In clustering, our goal is to group similar observations together and there are no specific pre-determined class labels involved.