mlp_rm_neurons

logical value, if TRUE, information about removed neurons
will be printed on the console (FALSE by default)

report


This function removes redundant neurons from the network, i.e. hidden layers'
neurons that are not connected to neurons in the previous layer or the next
layer. If a neuron is not connected to neurons in the previous layer but
is connected to neurons in the next layer (effectively acts as an additional
bias), biases of neurons in the next layer are properly adjusted, therefore,
the resulting network behaves just like the initial one.


Provides an interface to kernel routines from the FCNN C++ library.
FCNN is based on a completely new Artificial Neural Network representation that
offers unmatched efficiency, modularity, and extensibility. FCNN4R provides
standard teaching (backpropagation, Rprop, simulated annealing, stochastic
gradient) and pruning algorithms (minimum magnitude, Optimal Brain Surgeon),
but it is first and foremost an efficient computational engine. Users can
easily implement their algorithms by taking advantage of fast gradient computing
routines, as well as network reconstruction functionality (removing weights
and redundant neurons, reordering inputs, merging networks). Networks can be
exported to C functions in order to integrate them into virtually any software
solution.

mlp_rm_neurons: Remove redundant neurons in a multilayer perceptron network

Description

Usage

Arguments

Value