2813 search results - page 1 / 563 » The Combining Classifier: To Train or Not to Train |
ICPR
2002
IEEE
14 years 5 months ago
2002
IEEE
When more than a single classifier has been trained for the same recognition problem the question arises how this set of classifiers may be combined into a final decision rule. Se...
ICPR
2008
IEEE
14 years 5 months ago
2008
IEEE
On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
IJCAI
2003
13 years 6 months ago
2003
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
NIPS
1996
13 years 5 months ago
1996
We have combined an artificial neural network (ANN) character classifier with context-driven search over character segmentation, word segmentation, and word recognition hypotheses...
LCN
2006
IEEE
13 years 10 months ago
2006
IEEE
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...