What is multicollinearity in the context of Multiple Linear Regression?
- Adding interaction effects
- High correlation among variables
- Lowering the bias of the model
- Reducing overfitting
Multicollinearity refers to a situation where two or more independent variables in a Multiple Linear Regression model are highly correlated with each other.
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