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» Generating Better Decision Trees
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ICDE
2009
IEEE
140views Database» more  ICDE 2009»
14 years 9 months ago
Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning
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,...
ICIC
2009
Springer
13 years 5 months ago
Towards a Better Understanding of Random Forests through the Study of Strength and Correlation
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...
Simon Bernard, Laurent Heutte, Sébastien Ad...
ICML
2004
IEEE
14 years 8 months ago
Sequential skewing: an improved skewing algorithm
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...
Soumya Ray, David Page
KDD
1999
ACM
185views Data Mining» more  KDD 1999»
13 years 12 months ago
Visual Classification: An Interactive Approach to Decision Tree Construction
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...
PAAPP
2006
85views more  PAAPP 2006»
13 years 7 months ago
A new metric splitting criterion for decision trees
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...
Dan A. Simovici, Szymon Jaroszewicz