gradInit {deepNN}R Documentation

gradInit function

Description

A function to initialise memory for the gradient.

Usage

gradInit(dim)

Arguments

dim

the dimensions of the network as stored from a call to the function network, see ?network

Value

memory space and structure for the gradient, initialised as zeros

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


[Package deepNN version 1.2 Index]