Consider f_θ to be a probability density function with parameter θ. A set of k populations can now be defined such that the ith population Π_i is the set of density functions  . This paper proposes a test, based on the ϕ-dissimilarity, of the hypothesis that a new individual from a population Π₀ with a density function  , belongs to the ith population. The probabilities of misclassification of the minimum ϕ-dissimilarity classification rule are also obtained. In this paper, it is assumed that the parameters   and may be θ₀ are unknown and must be estimated from a set of training samples. Explicit expressions for the hypothesis test and the probabilities of misclassification are derived for the case where the populations Π_i consist of homoscedastic normal, as well as for gamma distributions.