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» Learning Classifiers from Semantically Heterogeneous Data
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HIS
2004
13 years 9 months ago
Classification Ensembles for Shaft Test Data: Empirical Evaluation
: A-scans from ultrasonic testing of long shafts are complex signals. The discrimination of different types of echoes is of importance for non-destructive testing and equipment mai...
Kyungmi Lee, Vladimir Estivill-Castro
JCP
2006
78views more  JCP 2006»
13 years 7 months ago
Parameter Optimization of Kernel-based One-class Classifier on Imbalance Learning
Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to le...
Ling Zhuang, Honghua Dai
ICML
2004
IEEE
14 years 8 months ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
CVPR
2010
IEEE
13 years 5 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
RR
2010
Springer
13 years 6 months ago
KWilt: A Semantic Patchwork for Flexible Access to Heterogeneous Knowledge
Semantic wikis and other modern knowledge management systems deviate from traditional knowledge bases in that information ranges from unstructured (wiki pages) over semi-formal (ta...
Klara A. Weiand, Steffen Hausmann, Tim Furche, Fra...