114 search results - page 5 / 23 » Error Rejection in Linearly Combined Multiple Classifiers |
ECML
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
BMCBI
2007
13 years 7 months ago
2007
Background: The size and magnitude of the metabolome, the ratio between individual metabolites and the response of metabolic networks is controlled by multiple cellular factors. A...
MLDM
1999
Springer
13 years 11 months ago
1999
Springer
In the field of pattern recognition, multiple classifier systems based on the combination of the outputs of a set of different classifiers have been proposed as a method for the de...
MCS
2000
Springer
13 years 11 months ago
2000
Springer
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...
DMIN
2006
13 years 9 months ago
2006
- An ideal ensemble is composed of base classifiers that perform well and that have minimal overlap in their errors. Eliminating classifiers from an ensemble based on a criterion t...