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.
