getExecOutputs,DArch-method

A instance of the class <code><a href="/link/?package=darch&version=0.10.0" darch'="" data-mini-rdoc="darch::"></a>'>DArch</code>

darch

Returns the execution output list of the <code><a href="/link/?package=darch&version=0.10.0" darch'="" data-mini-rdoc="darch::"></a>'>DArch</code> object

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; doi: 10.1162/neco.2006.18.7.1527) and "Reducing the
dimensionality of data with neural networks" (G. E. Hinton, R. R.
Salakhutdinov; 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

Package for Deep Architectures and Restricted Boltzmann Machines

getExecOutputs,DArch-method function

A instance of the class <code><a href='<a href='DArch'></a>'>DArch</a></code>

Returns the execution output list of the <code><a href='<a href='DArch'></a>'>DArch</a></code> object

Returns the execution output list of the <code><a href='<a href='DArch'></a>'>DArch</a></code> object — getExecOutputs,DArch-method

Returns the execution output list of the <code><a href='<a href='DArch'></a>'>DArch</a></code> object

Returns the execution output list of the <code><a href="/link/?package=darch&version=0.10.0" darch'="" data-mini-rdoc="darch::"></a>'>DArch</code> object

getExecOutputs,DArch-method: Returns the execution output list of the `'>DArch` object

Description

Usage

Arguments

See Also