Catálogo de publicaciones - tesis
Título de Acceso Abierto
Índices de validación para algoritmos de agrupamiento
David Nazareno Campo Georgina Stegmayer Leandro Daniel Vignolo Omar Chiotti Javier Iván Murillo Silvia Schiaffino Diego Humberto Milone
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Resumen/Descripción – provisto por el repositorio digital
External validation indexes allow similarities between two clustering solutions to be quantified. With classical external indexes, it is possible to quantify how similar two disjoint clustering solutions are, where each object can only belong to a single cluster. However, in practical applications, it is common for an object to have more than one label, thereby belonging to overlapped clusters; for example, subjects that belong to multiple communities in social networks. In this thesis, we propose a new index based on an intuitive probabilistic approach that is applicable to overlapped clusters. Given that recently there has been a remarkable increase in the analysis of data with naturally overlapped clusters, this new index allows to comparing clustering algorithms correctly. After presenting the new index, experiments with artificial and real datasets are shown and analyzed. Results over a real social network are also presented and discussed. The results indicate that the new index can correctly measure the similarity between two partitions of the dataset when there are different levels of overlap in the analyzed clusters.Palabras clave – provistas por el repositorio digital
Overlapped clusters; External validation; Validation indexes; Cluster perturbation; Grupos solapados; Validación externa; Índices de validación; Perturbación de grupos
Disponibilidad
| Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No requiere | 2019 | Biblioteca Virtual de la Universidad Nacional del Litoral (SNRD) |
|
Información
Tipo de recurso:
tesis
Idiomas de la publicación
- español castellano
País de edición
Argentina
Fecha de publicación
2019-05-30