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2 changes: 1 addition & 1 deletion predictive-modeling.md
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Expand Up @@ -19,7 +19,7 @@
- Solution to covariate shift
- importance weighted cv
#### 3. What are some ways I can make my model more robust to outliers?
- We can have regularization such as L1 or L2 to reduce variance (increase bias).
- We can have regularization such as L1 to reduce variance (increase bias).
- Changes to the algorithm:
- Use tree-based methods instead of regression methods as they are more resistant to outliers. For statistical tests, use non parametric tests instead of parametric ones.
- Use robust error metrics such as MAE or Huber Loss instead of MSE.
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