• Models the relationship between a scalar response and one or more explanatory variables. A fitted linear regression model can be used to identify the relationship between a single predictor variable xj and the response variable y when all the other predictor variables in the model are held fixed.

Is a:

• method

Applications:

• Feature Importance
• Price Prediction
• Regression
• Time Series Forecasting

Advantages:

• interpretable
• very simple
• widely used

Disadvantages:

• Assumes constant variance (homoscedasticity)
• Assumes independence of errors
• loses interpretability when there are more than a few features. Lasso can help with this.
• non-linearity has to be hand-crafted