1766 search results - page 16 / 354 » Classifier Selection Based on Data Complexity Measures |
PRL
2008
13 years 7 months ago
2008
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the comb...
BMCBI
2010
13 years 4 months ago
2010
Background: The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of ...
DEXA
2003
Springer
14 years 19 days ago
2003
Springer
In this paper, we propose a new feature selection criterion. It is based on the projections of data set elements onto each attribute. The main advantages are its speed and simplici...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
ADBIS
2009
Springer
13 years 11 months ago
2009
Springer
Data classification is usually based on measurements recorded at the same time. This paper considers temporal data classification where the input is a temporal database that descri...