403 search results - page 3 / 81 » Bayesian cluster ensembles |
MCS
2000
Springer
14 years 25 days ago
2000
Springer
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
GFKL
2004
Springer
14 years 2 months ago
2004
Springer
Cluster ensembles are collections of individual solutions to a given clustering problem which are useful or necessary to consider in a wide range of applications. The R package˜c...
SDM
2008
SIAM
13 years 10 months ago
2008
SIAM
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
KBS
2006
13 years 9 months ago
2006
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
ISMIS
2005
Springer
14 years 2 months ago
2005
Springer
Recently, there are many researchers to design Bayesian network structures using evolutionary algorithms but most of them use the only one fittest solution in the last generation. ...