The Decision Boundaries calculated through Bayes Theorem.
ClassifyByDecisionBoundaries(Data,DecisionBoundaries,ClassLabels)vector of Data
decision boundaries, BayesDecisionBoundaries
Optional numbered class labels that are assigned to the classes. default (1:L), L number of different components of gaussian mixture model
Cls(1:n,1:d) classiffication of Data, such that 1= first component of gaussian mixture model, 2= second component of gaussian mixture model and so on. For Every datapoint a number is returned.
Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Pattern classification. 2nd. Edition. New York, p. 512ff