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autoencodervspca

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Qaswara98 / Thesis_PCA_vs_AE

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This project is a comparative study of Autoencoder (AE) and Principal Component Analysis (PCA) for dimensionality reduction in gene expression data. It aims to understand the unique capabilities and applications of both methods in handling high-dimensional biological data.

machine-learning bioinformatics ae pca dimensionality-reduction autoencoders bioinformatics-tool geneexpression autoencodervspca
  • Updated May 25, 2024
  • Jupyter Notebook

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