dbn.train: Training a Deep Belief Net

In DimitriF/DLC: Deep Layer Chromatography

Description

Training a Deep Belief Net

Usage

dbn.train(x, hidden = c(10, 10), numepochs = 3, batchsize = 100,
  learningrate = 0.8, learningrate_scale = 1, momentum = 0.5,
  visible_type = "bin", hidden_type = "bin", cd = 1)

Arguments

x	matrix of x values for examples
hidden	number of hidden units
numepochs	number of iteration for samples Default is 3.
batchsize	size of mini-batch. Default is 100.
learningrate	learning rate for gradient descent. Default is 0.8.
learningrate_scale	learning rate will be mutiplied by this scale after every iteration. Default is 1 .
momentum	momentum for gradient descent. Default is 0.5 .
visible_type	activation function of input unit.Only support "sigm" now
hidden_type	activation function of hidden unit.Only support "sigm" now
cd	number of iteration for Gibbs sample of CD algorithm.

Author(s)

Xiao Rong

DimitriF/DLC documentation built on Oct. 14, 2020, 4:33 p.m.