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Here is some data separated by decision line

enter image description here

The equation of decision line/boundary is $x_1 -3x_2 + 3 = 0$. Therefore $w_1 = 1, w_2 = -3$ and, if $w_0 = -1$, then the bias $\theta = -3$.

Now, I have a question which states that the point $P = (2, 2)$ is being misclassified, and I have to explain why the perceptron algorithm will change weights upon hitting this point.

I really don't know how to do it. I also need to calculate the weights, but I don't know how to do it. Have I calculated the new weights correctly? Should I calculated them as follows?

$$w_{new} = w_{old} + error \times x = [1, -3] + (1-0) \times [2, 2] = [3, -1]$$

Therefore, the new equation of the decision boundary is $3x_1 - x_2 + 3 = 0$, where $w_1 = 3, w_2 = -1$, and $\theta= -3$. Is this correct?

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