par Bonet, Isis;Rodriguez, Abdel;Grau, Ricardo;García, María Matilde;Saez, Yvan;Nowe, Ann 
Référence Lecture notes in computer science, 5317 LNAI, page (90-99)
Publication Publié, 2008
Référence Lecture notes in computer science, 5317 LNAI, page (90-99)
Publication Publié, 2008
Article révisé par les pairs
| Résumé : | The selection of the distance measure to separate the objects of the knowledge space is critical in many classification algorithms. In this paper, we analyze the distance measures reported in the literature for the problem of HIV prediction. We propose a new distance for HIV viral sequences, based on the mutations with regard to the HXB2 reference sequence. In a first step, we reduce data dimensionality in order to subsequently analyze the distance measure's performance in terms of its ability to separate classes. © 2008 Springer Berlin Heidelberg. |
