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» Ensembles of Multi-Objective Decision Trees
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ECAI
2008
Springer
14 years 19 days ago
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo
BMCBI
2008
219views more  BMCBI 2008»
13 years 11 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
ECAI
2006
Springer
14 years 2 months ago
Ensembles of Grafted Trees
Grafted trees are trees that are constructed using two methods. The first method creates an initial tree, while the second method is used to complete the tree. In this work, the fi...
Juan José Rodríguez, Jesús Ma...
EICS
2010
ACM
14 years 4 months ago
Using ensembles of decision trees to automate repetitive tasks in web applications
Web applications such as web-based email, spreadsheets and form filling applications have become ubiquitous. However, many of the tasks that users try to accomplish with such web ...
Zachary Bray, Per Ola Kristensson
ROCAI
2004
Springer
14 years 4 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