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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 by Scipion
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