image thumbnail

Self-Adaptive-Synthetic-Over-Sampling-Approach

version 1.0.0 (142 KB) by X.Gu&P.Angelov
The MATLAB code for the research paper titled "A self‐adaptive synthetic over‐sampling technique for imbalanced classification".

34 Downloads

Updated 06 Mar 2020

From GitHub

View license on GitHub

This code is the self-adaptive synthetic over-sampling (SASYNO) approach described in:

X. Gu, P. Angelov, E Soares "A self-adaptive synthetic over-sampling technique for imbalanced classification,"
International Journal of Intelligent Systems, DOI: 10.1002/int.22230, 2020.

Please cite the paper above if this code helps.

For any queries about the code, please contact Dr. Xiaowei Gu, Prof. Plamen Angelov and Mr. Eduardo Soares
{x.gu3,p.angelov,e.almeidasoares}@lancaster.ac.uk

Programmed by Xiaowei Gu

Cite As

X. Gu, P. Angelov, E Soares "A self-adaptive synthetic over-sampling technique for imbalanced classification," International Journal of Intelligent Systems, DOI: 10.1002/int.22230, 2020.

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.