We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
A learner's performance does not rely only on the representation language and on the algorithm inducing a hypothesis in this language. Also the way the induced hypothesis is ...
The whole computer hardware industry embraced multicores. For these machines, the extreme optimisation of sequential algorithms is no longer sufficient to squeeze the real machine ...
Marco Aldinucci, Salvatore Ruggieri, Massimo Torqu...
Abstract. We present a new classification algorithm that combines three properties: It generates decision trees, which proved a valuable and intelligible tool for classification an...
We consider the problem of constructing decision trees for entity identification from a given relational table. The input is a table containing information about a set of entities...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Samb...