> For the complete documentation index, see [llms.txt](https://seattle-university.gitbook.io/sdgne/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://seattle-university.gitbook.io/sdgne/smote-variants.md).

# SMOTE Variants

SMOTE, abbreviated as Synthetic Minority Oversampling Technique, is used to generate synthetic data from the original dataset. Over the years, several variants of SMOTE have been developed, each tailored to specific scenarios and requirements. These variants employ distinct methodologies and innovations to enhance the generation of synthetic data, thereby improving model performance by ensuring a more balanced distribution of classes. We provide below. provided SMOTE variants for synthetic data generation. 

<table data-view="cards"><thead><tr><th></th><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td></td><td>               SMOTE</td><td></td><td><a href="/sdgne/smote-variants/smote.md">SMOTE</a></td></tr><tr><td></td><td>     Gamma SMOTE</td><td></td><td><a href="/sdgne/smote-variants/gamma-smote.md">Gamma SMOTE</a></td></tr><tr><td></td><td>      Gaussian SMOTE</td><td></td><td><a href="/sdgne/smote-variants/gaussian-smote.md">Gaussian SMOTE</a></td></tr><tr><td></td><td>          SDD SMOTE</td><td></td><td><a href="/sdgne/smote-variants/sdd-smote.md">SDD SMOTE</a></td></tr><tr><td></td><td>        ANVO SMOTE</td><td></td><td><a href="/sdgne/smote-variants/anvo-smote.md">ANVO SMOTE</a></td></tr><tr><td></td><td>SDD SMOTE (with incremental boosting)</td><td></td><td><a href="/sdgne/smote-variants/sdd-smote-with-incremental-boosting.md">SDD SMOTE with incremental boosting</a></td></tr></tbody></table>