Name
Abstract | ||
|---|---|---|
A common approach in many classification tasks consists in reducing the costs by turning as many errors as possible into rejects. This can be accomplished by introducing a reject rule which, working on the reliability of the decision, aims at increasing the performance of the classification system. When facing multiclass classification, Error Correcting Output Coding is a diffused and successful technique to implement a system by decomposing the original problem into a set of two class problems. The novelty in this paper is to consider different levels where the reject can be applied in the ECOC systems. A study for the behavior of such rules in terms of Error-Reject curves is also proposed and tested on several benchmark datasets. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-24085-0_13 | ICIAP (1) |
Keywords | Field | DocType |
classification system,different level,classification task,benchmark datasets,multiclass classification,error-reject curve,error correcting output coding,class problem,ecoc system,common approach | Computer science,Coding (social sciences),Artificial intelligence,Novelty,Machine learning,Multiclass classification | Conference |
Volume | ISSN | Citations |
6978 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. Simeone | 1 | 28 | 3.56 |
| Claudio Marrocco | 2 | 84 | 17.53 |
| Francesco Tortorella | 3 | 370 | 43.39 |