Methods for learning classifier combinations
Dmitriy Fradkin, Paul B. Kantor · 2005
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.