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» On Classifier Domains of Competence
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PRL
2006
98views more  PRL 2006»
14 years 9 months ago
Data complexity assessment in undersampled classification of high-dimensional biomedical data
Regularized linear classifiers have been successfully applied in undersampled, i.e. small sample size/high dimensionality biomedical classification problems. Additionally, a desig...
Richard Baumgartner, Ray L. Somorjai
LREC
2010
206views Education» more  LREC 2010»
14 years 11 months ago
Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain
In this paper we evaluate the performance of multilabel classification algorithms on the EUR-Lex database of legal documents of the European Union. On the same set of underlying d...
Eneldo Loza Mencía, Johannes Fürnkranz
BMCBI
2010
224views more  BMCBI 2010»
14 years 10 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
GECCO
2006
Springer
140views Optimization» more  GECCO 2006»
15 years 1 months ago
A representational ecology for learning classifier systems
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
James A. R. Marshall, Tim Kovacs
EMNLP
2009
14 years 7 months ago
Domain adaptive bootstrapping for named entity recognition
Bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retr...
Dan Wu, Wee Sun Lee, Nan Ye, Hai Leong Chieu