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PAA
2002
13 years 7 months ago
Bagging, Boosting and the Random Subspace Method for Linear Classifiers
: Recently bagging, boosting and the random subspace method have become popular combining techniques for improving weak classifiers. These techniques are designed for, and usually ...
Marina Skurichina, Robert P. W. Duin
CIDM
2009
IEEE
14 years 2 months ago
An empirical study of bagging and boosting ensembles for identifying faulty classes in object-oriented software
—  Identifying faulty classes in object-oriented software is one of the important software quality assurance activities. This paper empirically investigates the application of t...
Hamoud I. Aljamaan, Mahmoud O. Elish
ECAI
2008
Springer
13 years 9 months ago
Task Driven Coreference Resolution for Relation Extraction
Abstract. This paper presents the extension of an existing mimimally supervised rule acquisition method for relation extraction by coreference resolution (CR). To this end, a novel...
Feiyu Xu, Hans Uszkoreit, Hong Li
DAARC
2007
Springer
86views Algorithms» more  DAARC 2007»
14 years 1 months ago
Evaluating Hybrid Versus Data-Driven Coreference Resolution
Abstract. In this paper, we present a systematic evaluation of a hybrid approach of combined rule-based filtering and machine learning to Dutch coreference resolution. Through the...
Iris Hendrickx, Véronique Hoste, Walter Dae...
ICASSP
2008
IEEE
14 years 2 months ago
A weighted subspace approach for improving bagging performance
Bagging is an ensemble method that uses random resampling of a dataset to construct models. In classification scenarios, the random resampling procedure in bagging induces some c...
Qu-Tang Cai, Chun-Yi Peng, Chang-Shui Zhang