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» When Semi-supervised Learning Meets Ensemble Learning
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ICANN
2009
Springer
13 years 11 months ago
Statistical Instance-Based Ensemble Pruning for Multi-class Problems
Recent research has shown that the provisional count of votes of an ensemble of classifiers can be used to estimate the probability that the final ensemble prediction coincides w...
Gonzalo Martínez-Muñoz, Daniel Hern&...
PPSN
2004
Springer
14 years 1 days ago
Ensemble Learning with Evolutionary Computation: Application to Feature Ranking
Abstract. Exploiting the diversity of hypotheses produced by evolutionary learning, a new ensemble approach for Feature Selection is presented, aggregating the feature rankings ext...
Kees Jong, Elena Marchiori, Michèle Sebag
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
14 years 1 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof
PKDD
2004
Springer
155views Data Mining» more  PKDD 2004»
14 years 1 days ago
Ensemble Feature Ranking
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
Kees Jong, Jérémie Mary, Antoine Cor...
ICANN
2007
Springer
14 years 26 days ago
Boosting Unsupervised Competitive Learning Ensembles
Topology preserving mappings are great tools for data visualization and inspection in large datasets. This research presents a combination of several topology preserving mapping mo...
Emilio Corchado, Bruno Baruque, Hujun Yin