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» Learning Classifiers from Semantically Heterogeneous Data
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ECAI
2006
Springer
13 years 11 months ago
Semantic Tree Kernels to Classify Predicate Argument Structures
Recent work on Semantic Role Labeling (SRL) has shown that syntactic information is critical to detect and extract predicate argument structures. As syntax is expressed by means of...
Alessandro Moschitti, Bonaventura Coppola, Daniele...
SDM
2008
SIAM
133views Data Mining» more  SDM 2008»
13 years 9 months ago
Semantic Smoothing for Bayesian Text Classification with Small Training Data
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu
ICML
2002
IEEE
14 years 8 months ago
Is Combining Classifiers Better than Selecting the Best One
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...
Saso Dzeroski, Bernard Zenko
MCS
2005
Springer
14 years 29 days ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
ICDM
2003
IEEE
99views Data Mining» more  ICDM 2003»
14 years 22 days ago
Simple Estimators for Relational Bayesian Classifiers
In this paper we present the Relational Bayesian Classifier (RBC), a modification of the Simple Bayesian Classifier (SBC) for relational data. There exist several Bayesian classif...
Jennifer Neville, David Jensen, Brian Gallagher