Predict numeric values
Linear Regression builds relationship between inputs (features) and outputs (targets). It is a simple yet effective model to start with to get a benchmark.
- Using training data, the goal is to minimize the loss.
- You can measure loss function using SSE
Polynomial Regression: Linear Regression can also be used to model a non-linear relationship. To achieve this, we transform an input feature by a non-linear transformation function and create a new feature that can be used as input in the model.