There are several strategies to address high VIF values:
Remove highly correlated variables: Eliminate one of the variables that are highly correlated to reduce multicollinearity. Combine variables: Create a composite index or factor from highly correlated variables. Principal Component Analysis (PCA): Use PCA to transform correlated variables into a set of uncorrelated components. Ridge Regression: Apply ridge regression techniques to handle multicollinearity without removing variables.
