Supervised learning: Supervised learning is the learning of the model where with input variable ( say, x) and an output variable (say, Y) and an algorithm to map the input to the output.
That is, Y = f(X)
Unsupervised Learning: Unsupervised learning is where only the input data (say, X) is present and no corresponding output variable is there.
Here are the differences:
|Criteria||Supervised Learning||Unsupervised Learning|
|Input Data||Input data is labeled.||Input data is unlabelled.|
|Data Set||Uses training data set.||Uses the input data set.|
|Use||Use for prediction.||Use for analysis.|
|Enables||Enables classification & regression.||
Enables Classification, Density Estimation, & Dimension Reduction