You have found that your dataset has a high degree of multicollinearity. What steps would you consider to rectify this issue?
- Add more data points
- Increase the model bias
- Increase the model complexity
- Use Principal Component Analysis (PCA)
One way to rectify multicollinearity is to use Principal Component Analysis (PCA). PCA transforms the original variables into a new set of uncorrelated variables, thereby removing multicollinearity.
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