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 are shown in the table below. (These points correspond to the data point in the plot above)
Label -1 -1 -1 -1 -1 +1 +1 +1 +1 +1
Coordinates (0,0) (2,0) (3,0) (0,2) (2,2) (5,1) (5,2) (2,4) (4,4) (5,5)
Perceptron mistakes 1 9 10 5 9 11 0 3 1 1
Note: You should be able to arrive at the answer without programming.
What is the resulting offset parameter ?
Enter the numerical value for theta0 ?
What is the resulting parameter )?
(Enter as a vector, e.g. type [0,1] if theta = [0 1]^T)
2.
Setup as above: 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 are shown in the table below. (These points correspond to the data points in the plot above.)
Label -1 -1 -1 -1 -1 +1 +1 +1 +1 +1
Coordinates (0,0) (2,0) (3,0) (0,2) (2,2) (5,1) (5,2) (2,4) (4,4) (5,5)
Perceptron mistakes 1 9 10 5 9 11 0 3 1 1
The mistakes that the algorithm makes often depend on the order in which the points were considered. Could the point labeled have been the first one considered? yes or nor depends
3. Suppose that we now find the linear separator that maximizes the margin instead of running the perceptron algorithm.
What are the parameters and corresponding to the maximum margin separator?
(Enter theta0 accurate to at least 3 decimal places.)
(Enter theta as a vector, enclosed in square brackets, and components separated by commas, e.g. type [0,1] for[0 1]^T . )
4. What is the value of the margin attained?
(Enter an exact answer or decimal accurate to at least 2 decimal places.)
5. Using the parameters theta and theta0 corresponding to the maximum margin separator, what is the sum of Hinge losses evaluated on each example?
Sum of hinge losses: ?
6. Suppose we modify the maximum margin solution a bit and divide both theta and theta0 by 2. What is the sum of hinge losses evaluated on each example for this new separator?
Sum of hinge losses
1. th0 = -18
th = [4,4]
2)
no
3)
theta = [1,1]
theta_0 = -5
5)
sum_hinge_loss = 0
6)
sum_hinge_loss = 1.5
4)
1/norm||tetha|| = 1/sqrt(2)
There are 6 questions depends on same data.Pls hel answer
6) 11.5
1. th0 = -18
th = [7,6]
1) th_0 = -11
th = [3,2]
1)
theta = [-1,-1]
theta_0 = 5
1) th_0 = -17
th = [4, 4]