



Why is solution not exact when "fixed"
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Why is solution not exact when "fixed"Hi, I am using ActivationNetwork network = new ActivationNetwork( new BipolarSigmoidFunction(sigmoidAlphaValue), inputList.Count, inputList.Count, 1); BackPropagationLearning teacher = new BackPropagationLearning(network); With the same data for input AND output  just to see process of weights being set. So inputList.Count == 1; Why does the solution line, not match the data line exactly. They are the same data...
Re: Why is solution not exact when "fixed"Hello,
Network's weights are set randomly initially. Then you teach it to get result you need. Obviously it may take certain number of iterations for weights to converge to "optimal". Play with number of iterations, learning parameters ...
Re: Why is solution not exact when "fixed"Hi Andrew, I have actually tried all manner of variants of the parameters but I still never get to an exact match  is that because of the Sigmoid? I can't get better match than the picture above.
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