daltoolboxdp (version 1.2.737)

autoenc_conv_e: Convolutional Autoencoder - Encode

Description

Creates a deep learning convolutional autoencoder (ConvAE) to encode sequences of observations. Wraps a PyTorch implementation.

Usage

autoenc_conv_e(
  input_size,
  encoding_size,
  batch_size = 32,
  num_epochs = 1000,
  learning_rate = 0.001
)

Value

A autoenc_conv_e object.

Arguments

input_size

input size

encoding_size

encoding size

batch_size

size for batch learning

num_epochs

number of epochs for training

learning_rate

learning rate

References

Masci, J., Meier, U., Cireşan, D., & Schmidhuber, J. (2011). Stacked Convolutional Auto-Encoders.

Examples

if (FALSE) {
# Conv1D-based encoder expects data reshaped internally to (n, input_size, 1)
X <- matrix(rnorm(1000), nrow = 50, ncol = 20)
ae <- autoenc_conv_e(input_size = 20, encoding_size = 5, num_epochs = 50)
ae <- daltoolbox::fit(ae, X)
Z  <- daltoolbox::transform(ae, X)   # 50 x 5 encodings
}

# See:
# https://github.com/cefet-rj-dal/daltoolbox/blob/main/transf/autoenc_conv_e.md