Name
Title | ||
|---|---|---|
An Evolutionary Multiobjective Model and Instance Selection for Support Vector Machines With Pareto-Based Ensembles. |
Abstract | ||
|---|---|---|
Support vector machines (SVMs) are among the most powerful learning algorithms for classification tasks. However, these algorithms require a high computational cost during the training phase, which can limit their application on large-scale datasets. Moreover, it is known that their effectiveness highly depends on the hyper-parameters used to train the model. With the intention of dealing with the... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TEVC.2017.2688863 | IEEE Transactions on Evolutionary Computation |
Keywords | Field | DocType |
Support vector machines,Training,Evolutionary computation,Pareto optimization,Proposals,Computational efficiency | Training set,Mathematical optimization,Evolutionary algorithm,Computer science,Support vector machine,Evolutionary computation,Multi-objective optimization,Artificial intelligence,Boosting (machine learning),Instance selection,Pareto principle,Machine learning | Journal |
Volume | Issue | ISSN |
21 | 6 | 1089-778X |
Citations | PageRank | References |
9 | 0.52 | 50 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alejandro Rosales-Pérez | 1 | 79 | 8.80 |
| S. G. Garcia | 2 | 569 | 24.88 |
| JesúS A. GonzáLez | 3 | 132 | 12.22 |
| C. A. Coello Coello | 4 | 5799 | 427.99 |
| Francisco Herrera | 5 | 27391 | 1168.49 |