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» Results of the KDD'99 Classifier Learning
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ICML
2006
IEEE
14 years 8 months ago
Full Bayesian network classifiers
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
Jiang Su, Harry Zhang
ICMLC
2010
Springer
13 years 5 months ago
Optimization of bagging classifiers based on SBCB algorithm
: Bagging (Bootstrap Aggregating) has been proved to be a useful, effective and simple ensemble learning methodology. In generic bagging methods, all the classifiers which are trai...
Xiao-Dong Zeng, Sam Chao, Fai Wong
LREC
2008
128views Education» more  LREC 2008»
13 years 9 months ago
Relation between Agreement Measures on Human Labeling and Machine Learning Performance: Results from an Art History Domain
We discuss factors that affect human agreement on a semantic labeling task in the art history domain, based on the results of four experiments where we varied the number of labels...
Rebecca J. Passonneau, Thomas Lippincott, Tae Yano...
NIPS
2004
13 years 9 months ago
Boosting on Manifolds: Adaptive Regularization of Base Classifiers
In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the dat...
Balázs Kégl, Ligen Wang
COLING
2010
13 years 2 months ago
A Discriminative Latent Variable-Based "DE" Classifier for Chinese-English SMT
Syntactic reordering on the source-side is an effective way of handling word order differences. The (DE) construction is a flexible and ubiquitous syntactic structure in Chinese w...
Jinhua Du, Andy Way