Name
Abstract | ||
|---|---|---|
It is known that when dealing with interval-valued data, there exist problems associated with the non-existence of a total order. In this work we investigate a reformulation of an interval-valued decomposition strategy for multi-class problems called IVOVO, and we analyze the effectiveness of considering different admissible orders in the aggregation phase of IVOVO. We demonstrate that the choice of an appropriate admissible order allows the method to obtain significant differences in terms of accuracy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-29859-3_31 | HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2019 |
Keywords | Field | DocType |
Multi-class classification problems, One-vs-one strategy, Interval-valued fuzzy sets, Admissible order | Mathematical optimization,Computer science,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
11734 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mikel Uriz | 1 | 0 | 1.01 |
| Daniel Paternain | 2 | 237 | 26.18 |
| Humberto Bustince | 3 | 1938 | 134.10 |
| Mikel Galar | 4 | 1003 | 40.90 |