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» A Comparison of Decision Tree Ensemble Creation Techniques
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ICMLA
2008
13 years 6 months ago
Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous
Using decision trees that split on randomly selected attributes is one way to increase the diversity within an ensemble of decision trees. Another approach increases diversity by ...
Michael Gashler, Christophe G. Giraud-Carrier, Ton...
ROCAI
2004
Springer
13 years 10 months ago
An Empirical Evaluation of Supervised Learning for ROC Area
We present an empirical comparison of the AUC performance of seven supervised learning methods: SVMs, neural nets, decision trees, k-nearest neighbor, bagged trees, boosted trees,...
Rich Caruana, Alexandru Niculescu-Mizil
MCS
2009
Springer
13 years 9 months ago
Random Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data
Abstract. Data with multi-valued categorical attributes can cause major problems for decision trees. The high branching factor can lead to data fragmentation, where decisions have ...
Amir Ahmad, Gavin Brown
BMCBI
2010
109views more  BMCBI 2010»
13 years 4 months ago
Predicting gene function using hierarchical multi-label decision tree ensembles
Background: S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challe...
Leander Schietgat, Celine Vens, Jan Struyf, Hendri...
BMCBI
2008
219views more  BMCBI 2008»
13 years 4 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong