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Wiki/Machine Learning/Imbalanced Data.md
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@@ -11,5 +11,10 @@ Oversampling is when synthetic data is created for the minority class to equaliz
#### SMOTE #### SMOTE
The synthetic minority oversampling technique (SMOTE) is used to generate synthetic data to increase the size of a minority class. To create the synthetic data you: The synthetic minority oversampling technique (SMOTE) is used to generate synthetic data to increase the size of a minority class. To create the synthetic data you:
1. Choose a point in the minority class 1. Choose a point in the minority class
2. 2. Find k nearest minority neighbors
![[SMOTE.excalidraw]] 3. Select j of these neighbors
4. Create new synthetic data point along line between first point and selected neighbors
5. Repeat
![[SMOTE.excalidraw]]
### Algorithm-Level