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ML
2006
ACM
163views Machine Learning» more  ML 2006»
13 years 7 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
ACIVS
2007
Springer
13 years 11 months ago
Joint Domain-Range Modeling of Dynamic Scenes with Adaptive Kernel Bandwidth
Abstract. The first step in various computer vision applications is a detection of moving objects. The prevalent pixel-wise models regard image pixels as independent random process...
Borislav Antic, Vladimir S. Crnojevic
PR
2006
116views more  PR 2006»
13 years 7 months ago
Correspondence matching using kernel principal components analysis and label consistency constraints
This paper investigates spectral approaches to the problem of point pattern matching. We make two contributions. First, we consider rigid point-set alignment. Here we show how ker...
Hongfang Wang, Edwin R. Hancock
ICDM
2009
IEEE
124views Data Mining» more  ICDM 2009»
14 years 2 months ago
Rule Ensembles for Multi-target Regression
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...
Timo Aho, Bernard Zenko, Saso Dzeroski
PAMI
2007
166views more  PAMI 2007»
13 years 7 months ago
A Comparison of Decision Tree Ensemble Creation Techniques
Abstract—We experimentally evaluate bagging and seven other randomizationbased approaches to creating an ensemble of decision tree classifiers. Statistical tests were performed o...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...