For the perceptron algorithm, what will happen if I update weight vector for both correct and wrong prediction instead of just for wrong predictions? What will be the plot of number of wrong predictions look like w.r.t. number of passes? The algorithm of perceptron is the one proposed by Rosenblatt (1958) as below:
My question is that what will happen if we remove if condition and execute update for all instances in each pass.