Your Logistic Regression model is suffering from separation, causing some estimated Odds Ratios to be extremely large. How could you handle this issue?
- By adding more variables
- By applying regularization techniques
- By increasing the size of the dataset
- By removing all predictors
Separation in Logistic Regression can lead to overly large coefficient estimates. Applying regularization techniques, such as Ridge or Lasso, can help in constraining the coefficient estimates and mitigate this issue.
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