Which of the following statements are correct regarding supervised learning and unsupervised learning used to implement pattern recognition?

Supervised leaming depends on error detection, while unsupervised learning requires verification of the leamed function.

Supervised learning relies on labeled training data, while unsupervised learning discovers unknown patterns using algorithms.

An example of supervised learning is k$-$means, while an example of unsupervised learning is hierarchical clustering.

An example of supervised leaming is linear regression, while an example of unsupervised learning is naive Bayes.

Supervised leaming relies on single data points, while unsupervised leaming relies on data pairs consisting of inputs and resuliing outputs.