The em algorithm can be used to compute maximum likelihood estimates of model parameters for skew-t mixture models. We show that the intractable expectations needed in the e-step can be written out analytically. These closed form expressions bypass the need for numerical estimation procedures,...

Model-based clustering using a family of Gaussian mixture models, with parsimonious factor analysis like covariance structure, is described and an efficient algorithm for its implementation is presented. This algorithm uses the alternating expectation-conditional maximization (AECM) variant of...

The lift of an association rule is frequently used, both in itself and as a component in formulae, to gauge the interestingness of a rule. The range of values that lift may take is used to standardise lift so that it is more effective as a measure of interestingness. This standardisation is...