what is the decision boundary for gaussian? what is the decision boundary of a generative model why use the choice boundary in the generative model optimal decision boundary definition what is the optimal decision boundary what is the choice boundary in gaussian what is decision boundaries? if you use a mixture of gaussian distributions to determine if the probability is linear, then this is an optimal decision boundary which decision boundary would be optimal? why a decision boundary is not optimal which decision boundary is nonlinear and disjoint what is the best choice between linear and generative models? which of the following is not an optimal decision boundary which decision boundary is optimal? which is more difficult to find than a linear decision boundary why is the decision boundary nonlinear what is the decision boundary in a mixture of gaussian distributions which decision boundary is best described as a mixture of gaussian? what is the difference between a linear decision boundary and a discrete variable what's the generative model?