Linear models assume that the independent variables, X, take a linear relationship with the dependent variable, Y. This relationship can be dictated by the following equation:
Here, X specifies the independent variables and β are the coefficients that indicate a unit change in Y per unit change in X. Failure to meet this assumption may result in poor model performance.
Linear relationships can be evaluated by scatter plots and residual plots. Scatter plots output the relationship of the independent variable X and the target Y. Residuals are the difference between the linear estimation of Y using X and the real target:
If the relationship is linear, the residuals should follow a normal distribution centered at zero, while the values should vary homogeneously along the values of the independent variable. In this recipe, we...
