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raktim-mondol authored Aug 12, 2021
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In this project, we demonstrate how adversarial auto-encoder (AAE) model can be used to extract the features from high dimensional genetic (omics) data. We evaluated the performance of the model through twelve different supervised classifiers to verify the usefulness of the new features in breast cancer subtypes prediction.

![#c5f015](https://via.placeholder.com/15/c5f015/000000?text=+) `For biological insight please visit: https://github.com/NeuroSyd/latent-space-discovery`
![#c5f015](https://via.placeholder.com/15/c5f015/000000?text=+) For biological insight please visit: https://github.com/NeuroSyd/latent-space-discovery

![project_logo_transparent](https://user-images.githubusercontent.com/28592095/56498063-8039da00-6543-11e9-8b4a-a551bad3ed0f.png)

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