Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Random forest induction is a bagging method that randomly samples the feature set at each node in a decision tree. In propositional learning, the method has been shown to work well...
Celine Vens, Anneleen Van Assche, Hendrik Blockeel...
Consider a rooted tree T of arbitrary maximum degree d representing a collection of n web pages connected via a set of links, all reachable from a source home page represented by ...
The paper deals with the problem of reconstructing the tree-like topological structure of a network of linear dynamical systems. A distance function is defined in order to evaluat...
The main contribution of this paper is a bulk-loading algorithm for multi-way dynamic metric access methods based on the covering radius of a representative, like the Slim-tree. Th...