The Independency tree model: a new approach for clustering and factorisation.
M. Julia Flores, José Antonio Gámez, Serafı́n Moral · Probabilistic Graphical Models · 2006
Taking as an inspiration the so-called Explanation Tree for abductive inference in Bayesian networks, we have developed a new clustering approach. It is based on exploiting the variable independencies with the aim of building a tree structure such that in each leaf all the variables are independent. In this work we produce a structure called Independency tree. This structure can be seen as an extended probability tree, introducing a new and very important element: a list of probabilistic single potentials associated to every node. In the paper we will show that the model can be used to approximate a joint probability distribution and, at the same time, as a hierarchical clustering procedure. The Independency tree can be learned from data and it allows a fast computation of conditional probabilities.