Hi All,
I try to test the neural network package AMORE, I normalized my data first,
the input data is X [x1,x2,x3] where x1,x2,x3 each is 100 row 1 column
vector.
the output data Y is 100 row 1 column vector.
my network has neurons=c(3,2,2,1) which 2 hidden layers, 3 node in the
input layer while 1 in the output layer. Once the network is trained. I
use sim (result$net, z) to test the output,
Here z =c(0.01,0.09,-0.001842388), to my surprise, the simulation result
return is:
[,1]
[1,] -0.008967264
[2,] -0.008783412
[3,] -0.008750038
How come? It should return one scalar instead of a vector. Then I tried sim
(result$net, z2) which z2=c(0.01), the result return is:
[,1]
[1,] -0.008967264
As the input should have 3 variables, how come just one input variable can
have output value? And it is same as the first value in the result above.
Am I misunderstand something here? Many thanks
Ying
[[alternative HTML version deleted]]
