ADASYN (improves class balance, extension of SMOTE)
This submission implements the ADASYN (Adaptive Synthetic Sampling) algorithm as proposed in the following paper:
H. He, Y. Bai, E.A. Garcia, and S. Li, "ADASYN: Adaptive Synthetic Sampling Approach for Imbalanced Learning", Proc. Int'l. J. Conf. Neural Networks, pp. 1322-1328, (2008).
The purpose of the ADASYN algorithm is to improve class balance by synthetically creating new examples from the minority class via linear interpolation between existing minority class examples. This approach by itself is known as the SMOTE method (Synthetic Minority Oversampling TEchnique). ADASYN is an extension of SMOTE, creating more examples in the vicinity of the boundary between the two classes than in the interior of the minority class.
A demo script producing the title figure of this submission is provided.
Cite As
Dominic Siedhoff (2024). ADASYN (improves class balance, extension of SMOTE) (https://www.mathworks.com/matlabcentral/fileexchange/50541-adasyn-improves-class-balance-extension-of-smote), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
Tags
Acknowledgements
Inspired by: SMOTEBoost, SMOTE (Synthetic Minority Over-Sampling Technique)
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
Version | Published | Release Notes | |
---|---|---|---|
1.2.0.0 | [2015-04-23] improved quality of results in the presence of flat dimensions in the input data |
||
1.1.0.0 | ADASYN_upd1.zip [2015-04-21]:
|
||
1.0.0.0 |