One of the most challenging aspects of managing a very large data warehouse is identifying how queries will behave before they start executing. Yet knowing their performance charac...
Archana Ganapathi, Harumi A. Kuno, Umeshwar Dayal,...
In this paper we present a study on the Random Forest (RF) family of ensemble methods. From our point of view, a "classical" RF induction process presents two main drawba...
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...
Satisfying the basic requirements of accuracy and understandability of a classifier, decision tree classifiers have become very popular. Instead of constructing the decision tree ...
Mihael Ankerst, Christian Elsen, Martin Ester, Han...
Abstract: We examine a new approach to building decision tree by introducing a geometric splitting criterion, based on the properties of a family of metrics on the space of partiti...