deepNN (version 1.2)

nbiaspar: nbiaspar function

Description

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

Usage

nbiaspar(net)

Value

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

Arguments

net

an object of class network, see ?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()))
nbiaspar(net)