'Classifies the token into a cluster, returning
a probability distribution over the cluster identifiers.'

def classification_probdist(self, vector):

    likelihoods = {}
    sum = 0.0
    for cluster in self.cluster_names():
        likelihoods[cluster] = self.likelihood(vector, cluster)
        sum += likelihoods[cluster]
    for cluster in self.cluster_names():
        likelihoods[cluster] /= sum
    return DictionaryProbDist(likelihoods)
