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]]

