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» The Random Subspace Method for Constructing Decision Forests
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ICPR
2006
IEEE
14 years 8 months ago
Forest Extension of Error Correcting Output Codes and Boosted Landmarks
In this paper, we introduce a robust novel approach for detecting objects category in cluttered scenes by generating boosted contextual descriptors of landmarks. In particular, ou...
Oriol Pujol, Petia Radeva, Sergio Escalera
FCS
2006
13 years 9 months ago
Principles of Optimal Probabilistic Decision Tree Construction
Probabilistic (or randomized) decision trees can be used to compute Boolean functions. We consider two types of probabilistic decision trees - one has a certain probability to give...
Laura Mancinska, Maris Ozols, Ilze Dzelme-Berzina,...
HIPC
2005
Springer
14 years 1 months ago
Orthogonal Decision Trees for Resource-Constrained Physiological Data Stream Monitoring Using Mobile Devices
Several challenging new applications demand the ability to do data mining on resource constrained devices. One such application is that of monitoring physiological data streams ob...
Haimonti Dutta, Hillol Kargupta, Anupam Joshi
ECML
2007
Springer
13 years 11 months ago
Ensembles of Multi-Objective Decision Trees
Abstract. Ensemble methods are able to improve the predictive performance of many base classifiers. Up till now, they have been applied to classifiers that predict a single target ...
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzerosk...
ECCV
2010
Springer
14 years 1 months ago
Randomized Locality Sensitive Vocabularies for Bag-of-Features Model
Abstract. Visual vocabulary construction is an integral part of the popular Bag-of-Features (BOF) model. When visual data scale up (in terms of the dimensionality of features or/an...