In the SMOTE paper, the authors present the logic of creating synthetic examples when all features are nominal (section 6.2, SMOTE-N):
To generate new minority class feature vectors, we can create new set feature values by taking the majority vote of the feature vector in consideration and its k nearest neighbors
Along with this example:
Let F1 = A B C D E be the feature vector under consideration and let its 2 nearest neighbors be
F2 = A F C G N
F3 = H B C D N
The application of SMOTE-N would create the following feature vector: FS = A B C D N
How would FS be chosen in the case that F3 = H B C I N
? How does Value Difference Metric by Cost and Salzberg described in the paper assist in this case?