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SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 8 months ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard
ESANN
2006
13 years 8 months ago
Rotation-based ensembles of RBF networks
Abstract. Ensemble methods allow to improve the accuracy of classification methods. This work considers the application of one of these methods, named Rotation-based, when the clas...
Juan José Rodríguez, Jesús Ma...
ISMIS
2003
Springer
14 years 18 days ago
Evolutionary Computation for Optimal Ensemble Classifier in Lymphoma Cancer Classification
Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with ...
Chanho Park, Sung-Bae Cho
LREC
2010
165views Education» more  LREC 2010»
13 years 8 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
ICTAI
2008
IEEE
14 years 1 months ago
Ensemble Learning of Regional Classifiers
We present a new ensemble learning method that employs a set of regional classifiers, each of which learns to handle a subset of the training data. We split the training data and ...
Byungwoo Lee, Yong-chan Na, Byonghwa Oh, Jihoon Ya...