Compared to using PCA for dimensionality reduction, using a neural autoencoder has the big advantage that it works with source data that contains both numeric and categorical data, while PCA works ...

Creating and Training the LightGBM Autoencoder Model The LightGBM system does not have a built-in autoencoder class so one must be created using multiple regression modules. The goal of the ...

This method, known as GenoDrawing, involves training the autoencoder with a large dataset of apple images. The generated embeddings, along with SNP data, are then used to predict and reconstruct ...