What are the Limitations of Multiple Linear Regression?
Despite its utility, MLR has some limitations:
Multicollinearity: When independent variables are highly correlated, it can make estimates unreliable. Overfitting: Including too many variables can make the model fit the training data too well, reducing its generalizability. Assumption Violations: If the assumptions of MLR are not met, the results may be invalid.
