I'm programming a simple one layered perceptron.
For example, I have 3 neurons at the first layer, 2 at the second, and 2 at the output layer.
I have to solve a binary classification problem. This way I have 10 weights.
But I want to visualize the function that I get from this weights. E.g I want to plot function y = w0 + w1*x
So, the question is, which w0 and w1 are proper for this purpose?
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Rahul
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1I'm not sure if it's relevant, but this JS NN library has an option to convert your perceptron to a standalone function. https://github.com/wagenaartje/gynaptic – Thomas Wagenaar Mar 19 '17 at 11:15
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You do not get a single function. You can derive the decision function from the weights, but it's not a trivial combination of any pair of inputs; rather, it's that composition of the two layers of functions -- and then you subtract the values computed for class1 and class2; positive is one class, negative is the other.
If you want to plot the input weighting function for a particular perceptron, then you need to use the obvious w values, but I don't think this is what you're asking.
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Prune
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