MCS
2000
Springer
13 years 8 months ago
2000
Springer
MCS
2000
Springer
13 years 8 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...
MCS
2000
Springer
13 years 8 months ago
2000
Springer
Various methods exist for reducing correlation between classifiers in a multiple classifier framework. The expectation is that the composite classifier will exhibit improved perfor...
MCS
2000
Springer
13 years 8 months ago
2000
Springer
This paper presents a multi-expert system for dynamic signature verification. The system combines three experts whose complementar behaviour is achieved by using both different fea...
MCS
2000
Springer
13 years 8 months ago
2000
Springer
Abstract. A large experiment on combining classifiers is reported and discussed. It includes, both, the combination of different classifiers on the same feature set and the combina...
MCS
2000
Springer
13 years 8 months 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...
MCS
2000
Springer
13 years 8 months ago
2000
Springer
MCS
2000
Springer
13 years 8 months ago
2000
Springer
We introduce a mechanism for constructing and training a hybrid architecture of projection based units and radial basis functions. In particular, we introduce an optimization sche...
MCS
2000
Springer
13 years 8 months ago
2000
Springer
The use of multiple features by a classifier often leads to a reduced probability of error, but the design of an optimal Bayesian classifier for multiple features is dependent on t...