Problem 1. Linear Classification (4 pts)
Consider a labeled training set shown in the figure below:
oc -
(18)
We initialize the parameters to all zero values and run the linear perceptron algorithm through these points in a particular order until convergence. The number of mistakes made on each point is shown in the table below: (These points correspond to the data points in the plot above)
Label
Coordinates
(0,0) (2,0) (3,0) (0,2) (2,2) (5,1) (5,2) (2,4) (4,4) (5,5) Perceptron mistakes
Note: You should be able to arrive at the answer without programming:
What is the resulting offset parameter b?
Enter the numerical value for b:
What is the resulting parameter w?
Enter the numerical value for w: