Multi-class Classification Mu-Chun Su
Case I Each pattern class is separable from the other classes by a single hyperplane. M classes need M Perceptrons. A decision can not be made if (1) more than one perceptron have positive outputs; (2) none of the perceptron has positiveb output.
Case I
Case II Each pattern is separable from every other individual class by a distinct hyperplane. M classes need M(M-1)/2 perceptrons. If x belongs to w i then These hyperplanes have the property that
Case II
Case III There exist M hyperplanes with the property that if a pattern x belongs to the class w i. If the classes are separable under case 3 condition, they are automatically separable under Case 2. There exists no indeterminate region.
Case III