如何使用Neuronet包初始化权重？

Question

I am using the neuralnet package in R, but I have a problem when I want to initialize certain number of initial weights for my network. I have tried to do it based on the results that I got from the default random weights generated, but no luck at all.

This is the part where I should put the initial weights:

weigths<-c(-0.3,0.2,
    0.2,0.05,
    0,2,-0.1,
    -0.1,0.2,0.2)
net=neuralnet(to~x1+x2,tdata,hidden=2,threshold=0.01,constant.weights=weights) 

because I am considering that the weights follow this pattern:

Intercept.to.1layhid1  -5.0556934519949
x1.to.1layhid1         10.9208362719511
x2.to.1layhid1         12.9996270590530
Intercept.to.1layhid2   3.7047601228351
x1.to.1layhid2         -2.5636252939619
x2.to.1layhid2         -2.5759077405754
Intercept.to.to        -1.6494794336705
1layhid.1.to.to         1.3502874764968
1layhid.2.to.to         1.6969811621181

but when I apply it I got the error:

Error in constant.weights != 0

Any help?

Thanks

Answer 1

You are looking for the startweights argument to initialize custom weights. This is in the documentation:

help(neuralnet)

startweights:
  a vector containing starting values for the weights. 
  The weights will not be randomly initialized.

The constant.weights is used to specify fixed weights those which you would have excluded with the exclude agrument.