Repeat Problem 12.7, but use the following pattern classes: ω1: { (−1, 0)T, (0, −1)T, (1,...

Repeat Problem 12.7, but use the following pattern classes: ω1: { (−1, 0)T, (0, −1)T, (1, 0)T, (0, 1)T} and ω2: {(−2, 0)T, (0, − 2)T, (2, 0)T, (0, 2)T}. Observe that these classes are not linearly separable.

12.7 The following pattern classes have Gaussian probability density functions: ω1: {(0, 0)T, (2, 0)T, (2, 2 )T, (0, 2)T} and ω2: {(4, 4)T, (6, 4)T,(6, 6)T, (4, 6)T}.

(a) Assume that and obtain the equation of the Bayes decision boundary between these two classes.

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(b) Sketch the boundary.