SMOTE (Synthetic Minority Over-Sampling Technique)
The SMOTE (Synthetic Minority Over-Sampling Technique) function takes the feature vectors with dimension(r,n) and the target class with dimension(r,1) as the input.
And returns final_features vectors with dimension(r',n) and the target class with dimension(r',1) as the output.
Implementation based on :
N. Chawla, K. Bowyer, L. Hall, and W. Kegelmeyer. Smote: synthetic minority over-sampling technique. Arxiv preprint arXiv:1106.1813, 2011.
Cite As
Manohar (2024). SMOTE (Synthetic Minority Over-Sampling Technique) (https://www.mathworks.com/matlabcentral/fileexchange/38830-smote-synthetic-minority-over-sampling-technique), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Image Segmentation > Image Thresholding >
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Acknowledgements
Inspired: ADASYN (improves class balance, extension of SMOTE), SafeLevelSMOTE(original_features, original_mark)
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SMOTE/
Version | Published | Release Notes | |
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1.0.0.0 |