Name
Abstract | ||
|---|---|---|
There are numerous problems of increasing significance where a pattern can have several classes simultaneously associated. This kind of problems, usually called multi-label problems, should be tackled with specific techniques in order to generate models more accurate than those obtained with classical classification algorithms. This work presents the adaptation of the J48 algorithm to multi-label classification. The developed algorithm allows the generation of interpretable models and has been tested over several datasets and experiments show that it has a performance which is similar to other multi-label tree-based approaches being specially suitable to be used as base-classifier in an ensemble. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ISDA.2010.5687213 | Intelligent Systems Design and Applications |
Keywords | Field | DocType |
decision trees,learning (artificial intelligence),pattern classification,J48 algorithm,TDIDT technique,ensemble learning,multilabel classification,multilabel tree-based approach,J48,TDIDT,decision tree,multi-label | Decision tree,Algorithm design,Pattern recognition,Computer science,Multi-label classification,C4.5 algorithm,Artificial intelligence,Statistical classification,Ensemble learning,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4244-8134-7 | 0 | 0.34 |
References | Authors | |
9 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eva Lucrecia Gibaja Galindo | 1 | 28 | 3.37 |
| Manuel Victoriano | 2 | 0 | 0.34 |
| José Luis Ávila-Jiménez | 3 | 8 | 1.11 |
| S. Ventura | 4 | 2318 | 158.44 |
| Gibaja, E. | 5 | 0 | 0.34 |
| Avila-Jimenez, J.L. | 6 | 0 | 0.34 |