title: How do you draw a line using the weight vector in a Linear Perceptron?
body: <p>I understand the following:</p>
  
  <p>In 2D space, each data point has 2 features: x and y.
  The weight vector in 2D space contains 3 values [bias, w0, w1] which can be rewritten as [w0,w1,w2]. 
  Each datapoint needs an artificial coordinate [1, x, y] for the purposes of calculating the dot product between it and the weights vector.</p>
  
  <p>The learning rule used to update the weights vector for each misclassfied point is w := w + yn * xn </p>
  
  <p>My question is: how do you derive two points from the weight vector w = [A, B, C] in order to graph the decision boundary?</p>
  
  <p>I understand A + Bx + Cy = 0 is the linear equation in general form (A, B, C are can be taken from the weights vector) but I don't know how to plot it.</p>
  
  <p>Thanks in advance.</p>