Description Usage Arguments Value
Minimum magnitude pruning is a brute force, easy-to-implement pruning algorithm in which in each step the weight with the smallest absolute value is turned off. This algorithm requires reteaching network in almost every step and yields suboptimal results.
1 2 | mlp_prune_mag(net, input, output, tol_level, max_reteach_epochs, report,
plots = FALSE)
|
net |
an object of |
input |
numeric matrix, each row corresponds to one input vector, the number of columns must be equal to the number of neurons in the network input layer |
output |
numeric matrix with rows corresponding to expected outputs, the number of columns must be equal to the number of neurons in the network output layer, the number of rows must be equal to the number of input rows |
tol_level |
numeric value, error (MSE) tolerance level |
max_reteach_epochs |
integer value, maximal number of epochs (iterations) allowed when reteaching network |
report |
logical value, if TRUE, information about the pruning process will be printed on the console (FALSE by default) |
plots |
logical value, if TRUE, the initial network is plotted and then replotted every time neuron is removed and at the end of pruning (FALSE by default) |
Three-element list, the first field (net
) contains the pruned network,
the second (wcount
) - the number of connections removed (inactivated),
the third (ncount
) - the number of neurons removed.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.