22 search results - page 2 / 5 » Experiments on Ensembles with Missing and Noisy Data |
MCS
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
BMCBI
2006
13 years 4 months ago
2006
Background: Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performan...
NECO
2002
13 years 4 months ago
2002
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
ICASSP
2009
IEEE
13 years 2 months ago
2009
IEEE
Landmark multidimensional scaling (LMDS) uses a subset of data (landmark points) to solve classical MDS, where the scalability is increased but the approximation is noise-sensitiv...
ICDM
2005
IEEE
13 years 10 months ago
2005
IEEE
Ensemble methods have proved to be highly effective in improving the performance of base learners under most circumstances. In this paper, we propose a new algorithm that combine...