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» Methods for Dynamic Classifier Selection
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BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
ECOOP
1998
Springer
13 years 12 months ago
Predicate Dispatching: A Unified Theory of Dispatch
Predicate dispatching generalizes previous method dispatch mechanisms by permitting arbitrary predicates to control method applicability and by using logical implication between pr...
Michael D. Ernst, Craig S. Kaplan, Craig Chambers
ACL
2008
13 years 9 months ago
Active Sample Selection for Named Entity Transliteration
This paper introduces a new method for identifying named-entity (NE) transliterations within bilingual corpora. Current state-of-theart approaches usually require annotated data a...
Dan Goldwasser, Dan Roth
LREC
2010
165views Education» more  LREC 2010»
13 years 9 months ago
Maximum Entropy Classifier Ensembling using Genetic Algorithm for NER in Bengali
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on gen...
Asif Ekbal, Sriparna Saha
MCS
2002
Springer
13 years 7 months ago
Stacking with Multi-response Model Trees
We empirically evaluate several state-of-the-art methods for constructing ensembles of classifiers with stacking and show that they perform (at best) comparably to selecting the be...
Saso Dzeroski, Bernard Zenko