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CEC
2008
IEEE
15 years 3 months ago
Learning defect classifiers for visual inspection images by neuro-evolution using weakly labelled training data
This article presents results from experiments where a detector for defects in visual inspection images was learned from scratch by EANT2, a method for evolutionary reinforcement l...
Nils T. Siebel, Gerald Sommer
IJDMMM
2008
87views more  IJDMMM 2008»
15 years 1 months ago
Is an ordinal class structure useful in classifier learning?
In recent years, a number of machine learning algorithms have been developed for the problem of ordinal classification. These algorithms try to exploit, in one way or the other, t...
Jens C. Huhn, Eyke Hüllermeier
ICIP
2009
IEEE
14 years 11 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
IDEAL
2004
Springer
15 years 7 months ago
Learning to Classify Biomedical Terms Through Literature Mining and Genetic Algorithms.
We present an approach to classification of biomedical terms based on the information acquired automatically from the corpus of relevant literature. The learning phase consists of...
Irena Spasic, Goran Nenadic, Sophia Ananiadou
NLP
2000
15 years 5 months ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...