This is the code i tried :
net = newff(P,T,S)net = newff(P,T,S,TF,BTF,BLF,PF,IPF,OPF,DDF)
Description
newff(P,T,S) takes,
- P – RxQ1 matrix of Q1 representative R-element input vectors.
- T – SNxQ2 matrix of Q2 representative SN-element target vectors.
- Si – Sizes of N-1 hidden layers, S1 to S(N-1), default = [].
(Output layer size SN is determined from T.) and returns an N layer feed-forward backprop network.
This a description that i found .So i follow the instructions to create a neural network with one hidden layer composed of 6 nodes .
trainInput=[1 0.4 0.2 0.7]trainOutput=[0.8 ]chrom=[0.5 0.6 0.8 0.6 0.7 0.9 0.8 0.4 0.5 0.9 0.9; 0.1 0.7 0.6 0.7 0.9 0.5 0.9 0.2 0.4 0.5 0.9]; X=chrom(1,:);net=newff(minmax(trainInput'),trainOutput',6);trainInput = 1.0000 0.4000 0.2000 0.7000trainOutput = 0.8000>> net.IWans = [6x0 double] [] >> net.LWans = [] [] [0x6 double] []>> net.bans = [6x1 double] [0x1 double]
I didn't underdtand what does this notation means :
net.IWans = [6x0 double] []
it seems there is no connection with input ,i entered 4 input why i just have 2 cell ?
Best Answer