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» On Classifier Domains of Competence
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PRL
2006
98views more  PRL 2006»
13 years 7 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»
13 years 9 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»
13 years 7 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»
13 years 11 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
13 years 5 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