Let a minimum error classifier be used to recognize two-dimensional patterns from two classes, 1 0...

 

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Let a minimum error classifier be used to recognize two-dimensional patterns from two classes, 1 0 each having a normal distribution N(μr,r): M₁ = (3), 41-(1 3), . =(²3), V₁=(1 3), µ₂ =(3), 42=(√² 3). 0 Assume unit loss functions and a priori probabilities of classes: P(w₁) = P, P(w₂) = 1 - P. Determine and sketch the discrimination function in the two-dimensional feature space. (Points-10) Let a minimum error classifier be used to recognize two-dimensional patterns from two classes, 1 0 each having a normal distribution N(μr,r): M₁ = (3), 41-(1 3), . =(²3), V₁=(1 3), µ₂ =(3), 42=(√² 3). 0 Assume unit loss functions and a priori probabilities of classes: P(w₁) = P, P(w₂) = 1 - P. Determine and sketch the discrimination function in the two-dimensional feature space. (Points-10)