On Fri, 12 Sep 2003, Mark Kvale wrote: > a) AI::NeuralNet::Mesh - trains up multi-layer perceptrons, a type of > feedforward neural net. It has good documentation. For your problem, I > would reccommend a 3 layer net, with one input, one hidden and one > output layer, with tanh activation fuctions.
Perhaps a stupid question, but since we're on the subject of ANNs: What is a good criterion for choosing the number of nodes per layer? I haven't been up-to-date with ANN literature lately, but I recall reading that a 3-layer network should suffice most applications. Is that true? As for the nodes per layer, I would assume the input layer would have as many nodes as input variables, and the output layer will have as many nodes as the output var. What about the hidden layer(s)? --Ala
