I am attempting to use optim to solve a neural network problem. I would like
to optimize coefficients that are currently stored in a matrix
Y=270 x 1
X= 27- x 14
b1= 10x14
b2= 11x1
V= 10 x 14 set of prior variances.
I have the following function:
posterior.mode1=function(y,X,b_0,b2,V) {
log.like=function(b1) {
a_g=compute(b1)
z_g=tanh(a_g);
z_g=cbind(1,z_g)
p=softmax(z_g%*%b2);
a=sum(y*log(p)+(1-y)*log(1-p));
return(a);
}
compute=function(b1) {
a_g=NULL;
for(i in 1:nrow(b1)){
a_g=cbind(a_g,X%*%b1[i,])
}
return(a_g);
}
log.posterior=function(b1) {
-log.like(b1)+1/2*t(as.vector(b1))%*%diag(as.vector(V))%*%as.vector(b1)
}
a=optim(b_0,log.posterior,method="CG",hessian=TRUE)
return(a);
}
When I run
posterior.mode1(y,X,b1,b2,b1)
I get the following error
Error in 1:nrow(b1) : argument of length 0
Any comments would be very helpful
Thanks
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