Decision tree cluster all states in the given itemList and tie them as macroi where i is 1,2,3,.... This command performs a top down clustering of the states or models appearing in itemlist. This clustering starts by placing all items in a single root node and then choosing a question from the current set to split the node in such a way as to maximise the likelihood of a single diagonal covariance Gaussian at each of the child nodes generating the training data. This splitting continues until the increase in likelihood falls below threshold f or no questions are available which do not pass the outlier threshold test. This type of clustering is only implimented for single mixture, diagonal covariance untied models.