View source: R/autoencoder_denoising.R
autoencoder_denoising | R Documentation |
A denoising autoencoder trains with noisy data in order to create a model able to reduce noise in reconstructions from input data
autoencoder_denoising( network, loss = "mean_squared_error", noise_type = "zeros", ... )
network |
Layer construct of class |
loss |
Loss function to be optimized |
noise_type |
Type of data corruption which will be used to train the autoencoder, as a character string. Available types:
|
... |
Extra parameters to customize the noisy filter:
|
A construct of class "ruta_autoencoder"
Other autoencoder variants:
autoencoder_contractive()
,
autoencoder_robust()
,
autoencoder_sparse()
,
autoencoder_variational()
,
autoencoder()
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