Synthetic Minority Over-sampling Technique (SMOTE)

Synthetic Minority Over-sampling Technique, DOI: https://doi.org/10.1613/jair.953
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Updated 7 May 2020

SMOTE: Synthetic Minority Over-sampling Technique
This function is based on the paper referenced (DOI) below - with a few additional optional functionalities.
DOI: https://doi.org/10.1613/jair.953

This function synthesizes new observations based on existing (input) data, and a k-nearest neighbor approach. If multiple classes are given as input, only neighbors within the same class are considered.
This function can be used to over-sample minority classes in a dataset to create a more balanced dataset.

Cite As

Bjarke Skogstad Larsen (2024). Synthetic Minority Over-sampling Technique (SMOTE) (https://github.com/dkbsl/matlab_smote/releases/tag/1.0), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0

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.