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» The Alternating Decision Tree Learning Algorithm
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ECAI
2008
Springer
14 years 11 months 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
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
ICIP
2003
IEEE
15 years 11 months ago
Inverse halftoning by decision tree learning
Inverse halftoning is the process to retrieve a (gray) continuous-tone image from a halftone. Recently, machinelearning-based inverse halftoning techniques have been proposed. Dec...
Hae Yong Kim, Ricardo L. de Queiroz
ROBOCUP
2004
Springer
111views Robotics» more  ROBOCUP 2004»
15 years 3 months ago
Realtime Object Recognition Using Decision Tree Learning
Abstract. An object recognition process in general is designed as a domain specific, highly specialized task. As the complexity of such a process tends to be rather inestimable, m...
Dirk Wilking, Thomas Röfer
SAC
2009
ACM
15 years 4 months ago
LEGAL-tree: a lexicographic multi-objective genetic algorithm for decision tree induction
Decision trees are widely disseminated as an effective solution for classification tasks. Decision tree induction algorithms have some limitations though, due to the typical strat...
Márcio P. Basgalupp, Rodrigo C. Barros, And...