Name
Abstract | ||
|---|---|---|
This work compares two approaches to finding effective topic-independent classifier combinations. We suggest a new federated approach and compare it against the global approach. Our results indicate that the relative effectiveness of these approaches depends on the measure used to evaluate them. We suggest explanations for these results. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1145/1066677.1066915 | SAC |
Keywords | Field | DocType |
clear winner,global approach,relative effectiveness,effective topic-independent classifier combination,new federated approach | Data mining,Computer science,Artificial intelligence,Classifier (linguistics),Machine learning,Federated Architecture | Conference |
ISBN | Citations | PageRank |
1-58113-964-0 | 1 | 0.38 |
References | Authors | |
8 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dmitriy Fradkin | 1 | 344 | 19.25 |
| Paul Kantor | 2 | 3 | 0.76 |