Question

Supervised learning differs from unsupervised learning in that supervised learning requires

Answer 1

Supervised learning requires input and output.Machine is given training for every input through desired output. Targets are set and machine is trained through given input and output

In unsupervised learning we don't know about desired output.We give input and check the output for each target.It is used in clustering methods.

Answer 2

Supervised learning and unsupervised learning has the main difference in the data which they use in machine learning.

The subject of machine learning is quite complex.

Supervised learning is also more complex than unsupervised learning.

The third difference is accuracy.

Accuracy is more in supervised learning as compared with unsupervised learning.

Additionally, the classes used in supervised learning is known thus making the analysis predictable.