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» Agnostic Learning with Ensembles of Classifiers
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ICML
2002
IEEE
14 years 8 months ago
Is Combining Classifiers Better than Selecting the Best One
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...
Saso Dzeroski, Bernard Zenko
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
13 years 8 months ago
Class-Specific Ensembles for Active Learning
In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is...
Amit Mandvikar, Huan Liu
ESANN
2007
13 years 8 months ago
Ensemble neural classifier design for face recognition
A method for tuning MLP learning parameters in an ensemble classifier framework is presented. No validation set or cross-validation technique is required to optimize parameters for...
Terry Windeatt
IJON
2006
95views more  IJON 2006»
13 years 7 months ago
Ensemble classifiers based on correlation analysis for DNA microarray classification
Since accurate classification of DNA microarray is a very important issue for the treatment of cancer, it is more desirable to make a decision by combining the results of various ...
Kyung-Joong Kim, Sung-Bae Cho
CEC
2005
IEEE
13 years 9 months ago
On the use of rule-sharing in learning classifier system ensembles
This paper presents an investigation into exploiting the population-based nature of Learning Classifier Systems for their use within highly-parallel systems. In particular, the use...
Larry Bull, Matthew Studley, Anthony J. Bagnall, I...