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 |