| Título |
Association measures and aggregation functions |
| Tipo |
Congreso |
| Sub-tipo |
SCOPUS |
| Descripción |
Lecture Notes in Computer Science; 12th Mexican International Conference on Artificial Intelligence, MICAI 2013 |
| Resumen |
The concept of association measure generalizing the Pearson correlation coefficient is introduced. The methods of generation of association measures by means of pseudo-difference associated to some t-conorm and by similarity measures are proposed. The association measure can be introduced on any set with involutive reflection operation and suitably defined similarity measure. The methods of construction of association measures by Minkowski metric and data standardization using the aggregation functions are considered. The cosine similarity and the Pearson's correlation coefficient are obtained as partial cases of the proposed general methods. |
| Observaciones |
(including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Code 102536
DOI: 10.1007/978-3-642-45111-9_17
http://link.springer.com/chapter/10.1007/978-3-642-45111-9_17
|
| Lugar |
Distrito Federal |
| País |
Mexico |
| No. de páginas |
194-203 |
| Vol. / Cap. |
Volume 8266 LNAI, Issue PART 2 |
| Inicio |
2013-11-24 |
| Fin |
2013-11-30 |
| ISBN/ISSN |
978-364245110-2 |
