AutoEncoderModel: AutoEncoderModel

In resautonet: Autoencoder-based Residual Deep Network with Keras Support

Description

This function is to construct a residual autoencoder-based deep network.

Usage

AutoEncoderModel(nfea, nout, nodes, acts, mdropout = 0, reg = NULL,
  batchnorm = TRUE, isres = TRUE, outtype = 0, fact = "linear")

Arguments

nfea	integer, Number of features
nout	integer, Number of output units
nodes	list of integers, list of the number of nodes for the hidden layers in encoding component
acts	list of strings, list of activation function names
mdropout	double, dropout rate of the coding (middle) layer (default:0)
reg	string, regularization string (default: NULL)
batchnorm	bool, flag to conduct batch normalization (default:TRUE)
isres	bool, flag to conduct the residual connections (default: TRUE)
outtype	integer, output type, 0 indicating nout outputs and 1 nout+nfea outputs (default: 0)
fact	string, activation for output layer (default:"linear")

Value

keras model, model of (residual) autoencoder-based deep network

resautonet documentation built on May 2, 2019, 8:55 a.m.