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The following 1 0 instances are marked as positive ( Pi ) and negative ( Ni ) . A single Perceptron is used to divide

The following 10 instances are marked as positive (Pi) and negative (Ni). A single Perceptron is
used to divide the input space into two classes based on the instances. The resulting decision
boundary/hyperplane is shown in Figure 2.
P1=(4,1)
P2=(2,1)
P3=(2,2)
P4=(5,5)
P5=(3,2)
N1=(3,4)
N2=(1,1)
N3=(3,6)
N4=(3,1)
N5=(2,3)
The cut-off points of the hyperplane are at (0,1.25) and (-1,0).
4
COS4852/A2
x
y
(-1,0)
(0,1.25)
-5-4-3-2-1123456
-3
-2
-1
1
2
3
4
5
6
P1
P2
P3
P4
P5
N1
N2
N3
N4
N5

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