Imbalanced Supervised Classification Algorithm

An Imbalanced Supervised Classification Algorithm is a Supervised Classification Algorithm that is designed to handle an Imbalanced Training Dataset.

• Context:
  • It can be a Sampling-based Algorithm (make use of a Sampling Algorithm).
• Example(s):
  • SMOTE Algorithm.
• See: Balanced Supervised Classification Algorithm, Multiclass Supervised Classification Algorithm.

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References

2004

• (Chawla et al., 2004) ⇒ Nitesh Chawla, Nathalie Japkowicz, Aleksander Kolcz. (2004). “Editorial: Special issue on learning from imbalanced data sets.” In: ACM SIGKDD Explorations Newsletter, 6(1). doi:10.1145/1007730.1007733
• (Wu & Chang, 2004) ⇒ Gang Wu, and Edward Y. Chang. (2004). “Aligning Boundary in Kernel Space for Learning Imbalanced Dataset.” In: Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM 2004) doi:10.1109/ICDM.2004.10106

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