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Comparison of Decision Tree, Random Foreset and Random Forest with undersampled bootstrap for unbalanced data

Note:

This example shows class imbalance of ~200 ( dominant y=0 ).

  • Precision is always low
  • Using 'class_weight' in Random Forest seems to perform worse with more trees
  • Instead, explicit under-sampling dominant class (y=0) before bootstrap works for Random Forest with more trees

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