Scipion 0 Posted October 22, 2011 Share Posted October 22, 2011 (edited) Hi everyone, i'm a very beginner in Machine Learning and i hope that you can help me a bit. I'm working on Linear discriminants and i have to solve this problem : What are the values of weights : w0, w1, w2 for perceptron whose decision boundary is illustrated here : The decision boundary looks like a trivial function : 2/3x + 2 However, i don't know how to determine the weight. I know that : g(x) = W^t * X + w0 (where capital letters are vectors). when g(x)>0 : i decide omega1 g(x)<0 : omega2 g(x) = 0 : it corresponds to the decision boundary. In my set of datas, i have some label x1 and some label x2. (according to their positions) However, i don't know how to find the values for the weights. If anyone has an idea. Edited October 22, 2011 by Scipion Link to post Share on other sites

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