nnetpar: nnetpar function

In deepNN: Deep Learning

nnetpar function

Description

A function to calculate the number of weight parameters in a neural network, see ?network

Usage

nnetpar(net)

Arguments

net	an object of class network, see ?network

Value

an integer, the number of weight parameters in a neural network

References

1. Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach. Deep Learning. (2016)

2. Terrence J. Sejnowski. The Deep Learning Revolution (The MIT Press). (2018)

3. Neural Networks YouTube playlist by 3brown1blue: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

4. http://neuralnetworksanddeeplearning.com/

See Also

network, train, backprop_evaluate, MLP_net, backpropagation_MLP, logistic, ReLU, smoothReLU, ident, softmax, Qloss, multinomial, NNgrad_test, weights2list, bias2list, biasInit, memInit, gradInit, addGrad, nnetpar, nbiaspar, addList, no_regularisation, L1_regularisation, L2_regularisation

Examples

net <- network( dims = c(5,10,2),
                activ=list(ReLU(),softmax()))
nnetpar(net)

deepNN documentation built on Aug. 25, 2023, 5:14 p.m.