Displaying 1 result from an estimated 1 matches for "w_h1_o1".
2007 Jul 15
0
neural networks function in R
...maximize my likelihood. Another question here is how can I pass analytical gradient function of each of my network weight into the function? Specifically, my question is that does my gradient function has to be flat representation of each parameter like the following arbitrary example:
2*w_i1_h1+3*w_h1_o1+4 (where w_i1_h1 is weight of input node 1 to hidden layer node 1, and vice versa)
Or I can do a nest expression like:
sigmoid(node_eval(input_x, j))
here my node_eval is a function that takes in input_x feature value vector and produces output to node j in the next layer.
If expression base...