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» Ensembles of Multi-instance Learners
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ICPR
2004
IEEE
14 years 8 months ago
Nearest Neighbor Ensemble
Recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. The individual predictors (weak learners) can be very simple, ...
Bojun Yan, Carlotta Domeniconi
EMNLP
2007
13 years 8 months ago
Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles
We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...
Kenji Sagae, Jun-ichi Tsujii
TAL
2010
Springer
13 years 5 months ago
Robust Semi-supervised and Ensemble-Based Methods in Word Sense Disambiguation
Mihalcea [1] discusses self-training and co-training in the context of word sense disambiguation and shows that parameter optimization on individual words was important to obtain g...
Anders Søgaard, Anders Johannsen
IJSI
2008
156views more  IJSI 2008»
13 years 7 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
ICDM
2006
IEEE
84views Data Mining» more  ICDM 2006»
14 years 1 months ago
Exploratory Under-Sampling for Class-Imbalance Learning
Under-sampling is a class-imbalance learning method which uses only a subset of major class examples and thus is very efficient. The main deficiency is that many major class exa...
Xu-Ying Liu, Jianxin Wu, Zhi-Hua Zhou