56 search results - page 5 / 12 » Optimal ensemble construction via meta-evolutionary ensemble... |
MCS
2007
Springer
14 years 1 months ago
2007
Springer
A new scheme for the optimization of codebook sizes for HMMs and the generation of HMM ensembles is proposed in this paper. In a discrete HMM, the vector quantization procedure and...
GECCO
2003
Springer
14 years 21 days ago
2003
Springer
One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their si...
JMLR
2012
11 years 10 months ago
2012
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
Bagging is an ensemble method that uses random resampling of a dataset to construct models. In classification scenarios, the random resampling procedure in bagging induces some c...
DMIN
2008
13 years 9 months ago
2008
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...