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AUSAI
2005
Springer
13 years 10 months ago
Ensemble Selection for SuperParent-One-Dependence Estimators
SuperParent-One-Dependence Estimators (SPODEs) loosen Naive-Bayes’ attribute independence assumption by allowing each attribute to depend on a common single attribute (superpare...
Ying Yang, Kevin B. Korb, Kai Ming Ting, Geoffrey ...
PR
2010
158views more  PR 2010»
13 years 3 months ago
Out-of-bag estimation of the optimal sample size in bagging
The performance of m-out-of-n bagging with and without replacement in terms of the sampling ratio (m/n) is analyzed. Standard bagging uses resampling with replacement to generate ...
Gonzalo Martínez-Muñoz, Alberto Su&a...
JCNS
2006
69views more  JCNS 2006»
13 years 5 months ago
Effects of stimulus transformations on estimates of sensory neuron selectivity
Stimulus selectivity of sensory systems is often characterized by analyzing responseconditioned stimulus ensembles. However, in many cases these response-triggered stimulus sets h...
Alexander G. Dimitrov, Tomás Gedeon
CIDM
2009
IEEE
14 years 1 days ago
Ensemble member selection using multi-objective optimization
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
Tuve Löfström, Ulf Johansson, Henrik Bos...
IJON
2010
148views more  IJON 2010»
13 years 3 months ago
Modeling radiation-induced lung injury risk with an ensemble of support vector machines
Radiation-induced lung injury, radiation pneumonitis (RP), is a potentially fatal side-effect of thoracic radiation therapy. In this work, using an ensemble of support vector mac...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...