1. A method for object classification comprising: obtaining a set of hypercubes representing a set of rules for the object; associating a cost weight for each hypercube in said set of hypercubes; and building a search tree for said set of hypercubes by splitting intermediate tree nodes of said search tree based on a predicted future cost weight of child sub-trees within said search tree, wherein each node in said search tree includes decision dimension and a splitting threshold.