mlp_rm_neurons: Remove redundant neurons in a multilayer perceptron network
In FCNN4R: Fast Compressed Neural Networks for R
Description
Usage
Arguments
Value
Description
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.
Usage
1
mlp_rm_neurons(net, report = FALSE)
Arguments
net
an object of mlp_net class
report
logical value, if TRUE, information about removed neurons
will be printed on the console (FALSE by default)
Value
Three-element list. The first element (net) is the network
(an object of mlp_net class) with all redundant neurons
removed, the second (ncount) - the number of neurons removed,
the third (wcount) - the number of weights removed.
FCNN4R documentation built on May 29, 2017, 4:26 p.m.
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Description Usage Arguments Value
Description
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.
Usage
1 | mlp_rm_neurons(net, report = FALSE)
|
Arguments
net |
an object of |
report |
logical value, if TRUE, information about removed neurons will be printed on the console (FALSE by default) |
Value
Three-element list. The first element (net) is the network
(an object of mlp_net class) with all redundant neurons
removed, the second (ncount) - the number of neurons removed,
the third (wcount) - the number of weights removed.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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