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A monte carlo analysis of ensemble classification (2004)
| Content Provider | CiteSeerX |
|---|---|
| Author | Esposito, Roberto Saitta, Lorenza |
| Description | In this paper we extend previous results providing a theoretical analysis of a new Monte Carlo ensemble classifier. The framework allows us to characterize the conditions under which the ensemble approach can be expected to outperform the single hypothesis classifier. Moreover, we provide a closed form expression for the distribution of the true ensemble accuracy, as well as of its mean and variance. We then exploit this result in order to analyze the expected error behavior in a particularly interesting case. |
| File Format | |
| Language | English |
| Publisher | Morgan Kaufmann |
| Publisher Date | 2004-01-01 |
| Publisher Institution | IN: PROC. 23TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING |
| Access Restriction | Open |
| Subject Keyword | Monte Carlo Analysis Ensemble Classification Single Hypothesis Classifier New Monte Carlo Ensemble Classifier Closed Form Expression Ensemble Approach Theoretical Analysis Interesting Case Previous Result True Ensemble Accuracy Expected Error Behavior |
| Content Type | Text |
| Resource Type | Article |
