DArch-class

This class represents a model created, and/or configured, and/or trained with
the <code><a rd-options="" href="/link/darch?package=darch&version=0.12.0" data-mini-rdoc="darch::darch">darch</a></code> function.
It implements deep architectures and provides the ability to train 
them with a pre training using contrastive divergence and fine tuning with 
backpropagation, resilient backpropagation and conjugate gradients.

internal

The darch package is built on the basis of the code from G. E.
Hinton and R. R. Salakhutdinov (available under Matlab Code for deep belief
nets). This package is for generating neural networks with many layers (deep
architectures) and train them with the method introduced by the publications
"A fast learning algorithm for deep belief nets" (G. E. Hinton, S. Osindero,
Y. W. Teh (2006) <DOI:10.1162/neco.2006.18.7.1527>) and "Reducing the
dimensionality of data with neural networks" (G. E. Hinton, R. R.
Salakhutdinov (2006) <DOI:10.1126/science.1127647>). This method includes a
pre training with the contrastive divergence method published by G.E Hinton
(2002) <DOI:10.1162/089976602760128018> and a fine tuning with common known
training algorithms like backpropagation or conjugate gradients.
Additionally, supervised fine-tuning can be enhanced with maxout and
dropout, two recently developed techniques to improve fine-tuning for deep
learning.

Martin Drees

darch

Package for Deep Architectures and Restricted Boltzmann Machines

DArch-class function

<dl class="dl-horizontal">
<dt><code>rbmList</code></dt><dd>A list which contains all RBMs for the pre-training.</dd></dl><dt><code>layers</code></dt><dd>A list with the layer information. In the first field are the 
weights and in the second field is the unit function.</dd><dt><code>cancel</code></dt><dd>Boolean value which indicates if the network training is 
canceled.</dd><dt><code>cancelMessage</code></dt><dd>The message when the execution is canceled.</dd><dt><code>dropoutMasks</code></dt><dd>List of dropout masks, used internally.</dd><dt><code>dataSet</code></dt><dd><a href="/link/?package=darch&version=0.12.0" dataset'="" data-mini-rdoc="darch::"></a>'>DataSet instance.</dd>

Slots

This class represents a model created, and/or configured, and/or trained with
the <code><a rd-options='' href='darch'>darch</a></code> function.
It implements deep architectures and provides the ability to train 
them with a pre training using contrastive divergence and fine tuning with 
backpropagation, resilient backpropagation and conjugate gradients.

DArch-class: Class for deep architectures

Description

Arguments

Slots

Details

See Also