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» When Semi-supervised Learning Meets Ensemble Learning
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ML
2002
ACM
127views Machine Learning» more  ML 2002»
14 years 9 months ago
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combinations of base hypotheses generat...
Gunnar Rätsch, Ayhan Demiriz, Kristin P. Benn...
84
Voted
ESANN
2006
14 years 11 months ago
Immune Network based Ensembles
This paper presents a new method for constructing ensembles of classifiers based on immune network theory, one of the most interesting paradigms within the field of artificial imm...
Nicolás García-Pedrajas, Colin Fyfe
GCB
2003
Springer
164views Biometrics» more  GCB 2003»
15 years 2 months ago
Integrative machine learning approach for multi-class SCOP protein fold classification
: Classification and prediction of protein structure has been a central research theme in structural bioinformatics. Due to the imbalanced distribution of proteins over multi SCOP ...
Aik Choon Tan, David Gilbert, Yves Deville
66
Voted
ICML
2006
IEEE
15 years 10 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
IJCAI
2003
14 years 11 months ago
Constructing Diverse Classifier Ensembles using Artificial Training Examples
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Prem Melville, Raymond J. Mooney