The major difference between Regression and Classification is that Regression results in a continuous quantitative value while Classification is predicting the discrete labels.
However, there is no clear line that draws the difference between the two. We have a few properties of both Regression and Classification. These are as follows:
- Regression predicts the quantity.
- We can have discrete as well as continuous values as input for regression.
- If input data are ordered with respect to the time it becomes time series forecasting.
- The Classification problem for two classes is known as Binary Classification.
- Classification can be split into Multi- Class Classification or Multi-Label Classification.
- We focus more on accuracy in Classification while we focus more on the error term in Regression.