mlp_net-manipulating-network-inputs: Manipulating network inputs
In FCNN4R: Fast Compressed Neural Networks for R

Description Usage Arguments Value Examples

These functions construct new network by removing redundant (i.e. not connected to the next layer) inputs or reordering / expanding network inputs.

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mlp_rm_input_neurons(net, report = FALSE)

mlp_expand_reorder_inputs(net, newnoinputs, inputsmap)

`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)
`newnoinputs`	integer value, determines the number of inputs in the new network
`inputsmap`	integer vector, determines the mapping of old inputs into new ones - the ith value of this vector will be the new index of ith input

mlp_rm_input_neurons returns a two-element list. The first element (net) is the network (an object of mlp_net class) with all redundant input neurons removed, the second (ind) - the indices of input neurons that were not removed.

mlp_expand_reorder_inputs returns an object of mlp_net class.

# construct a 2-4-3 network, plot result
nn <- mlp_net(c(2, 4, 3))
nn <- mlp_rnd_weights(nn)
mlp_plot(nn, TRUE)
# expand inputs, the new no. of inputs will be 5, with the first input
# becoming the 3rd and the second retaining its position, plot result
nn <- mlp_expand_reorder_inputs(nn, 5, c(3, 2))
mlp_plot(nn, TRUE)
# remove redundant neurons (i.e. 1, 4, 5) and plot result
nn <- mlp_rm_input_neurons(nn, TRUE)$net
mlp_plot(nn, TRUE)