Name
Abstract | ||
|---|---|---|
Properties of ensemble classification can be studied using the framework of Monte Carlo stochastic algorithms. Within this framework it is also possible to define a new ensemble classifier, whose accuracy probability distribution can be computed exactly. This paper has two goals: first, an experimental comparison between the theoretical predictions and experimental results; second, a systematic comparison between bagging and Monte Carlo ensemble classification. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1145/1102351.1102378 | ICML |
Keywords | Field | DocType |
accuracy probability distribution,monte carlo stochastic algorithm,systematic comparison,experimental comparison,new ensemble classifier,ensemble classification,theoretical prediction,monte carlo ensemble classification,probability distribution,monte carlo | Monte Carlo method in statistical physics,Monte Carlo method,Ensemble forecasting,Markov chain Monte Carlo,Computer science,Hybrid Monte Carlo,Monte Carlo integration,Artificial intelligence,Monte Carlo molecular modeling,Ensemble learning,Machine learning | Conference |
ISBN | Citations | PageRank |
1-59593-180-5 | 3 | 0.46 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Esposito | 1 | 64 | 10.87 |
| Lorenza Saitta | 2 | 966 | 302.98 |