Name
Abstract | ||
|---|---|---|
This paper demonstrates that several known sequence kernels can be expressed in a unified framework in which the position specificity is modeled by fuzzy equivalence relations. In addition to this interpretation, we address the practical issues of positive semidefiniteness, computational complexity, and the extraction of interpretable features from the final support vector machine classifier. |
Year | Venue | Keywords |
|---|---|---|
2009 | PROCEEDINGS OF THE JOINT 2009 INTERNATIONAL FUZZY SYSTEMS ASSOCIATION WORLD CONGRESS AND 2009 EUROPEAN SOCIETY OF FUZZY LOGIC AND TECHNOLOGY CONFERENCE | fuzzy equivalence relation, kernel, sequence classification, support vector machines |
Field | DocType | Citations |
Kernel (linear algebra),Definiteness,Fuzzy equivalence,Equivalence partitioning,Support vector machine classifier,Support vector machine,Theoretical computer science,Artificial intelligence,Fuzzy equivalence relation,Machine learning,Mathematics,Computational complexity theory | Conference | 1 |
PageRank | References | Authors |
0.37 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ulrich Bodenhofer | 1 | 705 | 68.02 |
| Karin Schwarzbauer | 2 | 1 | 0.37 |
| Mihaela Ionescu | 3 | 1 | 0.71 |
| S Hochreiter | 4 | 9471 | 440.12 |