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ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
14 years 4 months ago
Projective Clustering Ensembles
Recent advances in data clustering concern clustering ensembles and projective clustering methods, each addressing different issues in clustering problems. In this paper, we consi...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
14 years 4 months ago
Heuristic speciation for evolving neural network ensemble
Speciation is an important concept in evolutionary computation. It refers to an enhancements of evolutionary algorithms to generate a set of diverse solutions. The concept is stud...
Shin Ando
AAAI
2008
14 years 12 days ago
Constraint Projections for Ensemble Learning
It is well-known that diversity among base classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods obtain diverse individual learners through res...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou, Qiang ...
TNN
2010
127views Management» more  TNN 2010»
13 years 4 months ago
RAMOBoost: ranked minority oversampling in boosting
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Sheng Chen, Haibo He, Edwardo A. Garcia
IJCNN
2007
IEEE
14 years 4 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar