sigmUnitFuncSwitch

A instance of the class <code><a href="/link/RBM?package=darch&version=0.9.1" rd-options="" data-mini-rdoc="darch::RBM">RBM</a></code>.

A list with the data matrices for the
  calculations.

dataList

biases

weights

Parameters which indicates the status of
  the training. <code>"actualCD"</code> and <code>"finishCD"</code> are
  needed (see <code><a href="/link/trainRBM?package=darch&version=0.9.1" rd-options="" data-mini-rdoc="darch::trainRBM">trainRBM</a></code>)

runParams

Calculates the neuron output with the sigmoid function
either from the real value or binary input saved in the
list <code>dataList</code>.

The darch package is build on the basis of the code from G. E.
    Hinton and R. R. Salakhutdinov (available under Matlab Code for deep belief
    nets : last visit: 01.08.2013). 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) and "Reducing the
    dimensionality of data with neural networks" (G. E. Hinton, R. R.
    Salakhutdinov). This method includes a pre training with the contrastive
    divergence method publishing by G.E Hinton (2002) and a fine tuning with
    common known training algorithms like backpropagation or conjugate
    gradient.

sigmUnitFuncSwitch: Calculates the neuron output with the sigmoid function

Description

Usage

Arguments

Value

Details

See Also