Name
Title | ||
|---|---|---|
Multi-objective evolutionary optimization for generating ensembles of classifiers in the ROC space |
Abstract | ||
|---|---|---|
In this paper, we propose a novel approach for the multi-objective optimization of classifier ensembles in the ROC space. We first evolve a pool of simple classifiers with NSGA-II using values of the ROC curves as the optimization objectives. These simple classifiers are then combined at the decision level using the Iterative Boolean Combination method (IBC). This method produces multiple ensembles of classifiers optimized for various operating conditions. We perform a rigorous series of experiments to demonstrate the properties and behaviour of this approach. This allows us to propose interesting venues for future research on optimizing ensembles of classifiers using multi-objective evolutionary algorithms. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2330163.2330285 | GECCO |
Keywords | Field | DocType |
classifier ensemble,novel approach,multi-objective optimization,roc space,multi-objective evolutionary optimization,optimization objective,simple classifier,roc curve,multi-objective evolutionary algorithm,iterative boolean combination method,decision level,operant conditioning,machine learning,multi objective optimization,genetic programming | Receiver operating characteristic,Ensembles of classifiers,Evolutionary algorithm,Decision level,Pattern recognition,Computer science,Random subspace method,Cascading classifiers,Genetic programming,Artificial intelligence,Classifier (linguistics),Machine learning | Conference |
Citations | PageRank | References |
10 | 0.51 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julien-Charles Levesque | 1 | 31 | 2.98 |
| Audrey Durand | 2 | 22 | 3.00 |
| Christian Gagné | 3 | 627 | 52.38 |
| Robert Sabourin | 4 | 908 | 61.89 |