Name
Abstract | ||
|---|---|---|
ANOVA decomposition is used as the basis for the develop- ment of a new wrapper feature subset selection method, in which functional networks are used as the induction algorithm. The performance of the pro- posed method was tested against several artificial and real data sets. The results obtained are comparable, and even better, in some cases, to those accomplished by other well-known methods, being the proposed algorithm faster. In this paper, a new wrapper subset selection algorithm based on ANOVA decomposition is presented. Functional networks are used as the induction al- gorithm. The method has been tested against several benchmark and real data sets, and their results are presented and compared with those obtained by other filter and wrapper algorithms. |
Year | Venue | Field |
|---|---|---|
2005 | ESANN | Data mining,Data set,Pattern recognition,Computer science,Selection algorithm,Functional networks,Artificial intelligence,Machine learning |
DocType | Citations | PageRank |
Conference | 2 | 0.46 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Noelia Sánchez-Maroño | 1 | 406 | 25.39 |
| Amparo Alonso-Betanzos | 2 | 885 | 76.98 |
| Enrique Castillo | 3 | 555 | 59.86 |