1. A model selection computer, comprising: a model optimization unit which optimizes a model for a mixed distribution; and an optimum distribution selection unit which selects a number of mixtures whose information criterion is optimum, wherein: the model optimization unit optimizes an expected information criterion of the complete data by setting a partial model and parameter, and related to an information criterion of complete data, said model optimization unit optimizes the expected information criterion of said complete data for a pair of a model and a parameter of a component which satisfies a predetermined condition by using an expected value of a hidden variable post-event distribution of said complete data, wherein the model selection computer further comprises: a number of mixtures setting unit which selects a candidate value yet to be optimized from among candidate values of the number of mixtures; a distribution initialization unit which executes initialization processing of data by using the number of mixtures selected by said number of mixtures setting unit; and a number of mixtures loop end determination unit which determines whether a value of an optimum information criterion is calculated with respect to each of candidate values of all the numbers of mixtures and when determining that not all the values are calculated, causes another execution of the processing by said number of mixtures setting unit, said distribution initialization unit and said model optimization unit; wherein: said model optimization unit includes: a hidden variable post-event distribution calculation unit which calculates a post-event distribution with respect to a hidden variable of said data; an update parameter setting unit which selects a pair of a model and a parameter of a component which satisfies a predetermined condition; a conditional expected information criterion optimization unit which, related to a post-event distribution calculated by said hidden variable post-event distribution calculation unit, optimizes an expected information criterion for complete data with respect to a pair of a model and a parameter selected by said update parameter setting unit; an information criterion calculation unit which calculates a value of an information criterion for incomplete data with respect to a model updated by optimization by said conditional expected information criterion optimization unit; and an optimality determination unit which determines optimality of a value of an information criterion calculated by said information criterion calculation unit and when determining that the value is not optimum, executes the optimization processing again, and the optimum distribution selection unit selects a type of mixed components whose information criterion is optimum, and compares values of information criteria calculated with respect to candidate values of all the numbers of mixtures to select both the number of mixtures and the kind of mixtures whose information criterion is optimum.