Técnicas de agrupamiento para métricas en difractogramas
In the present thesis starting from the dissimilarity introduced by Nicolás López, non-supervised algorithms are applied with the objective of finding natural groupings in the data of diffractograms and obtaining visual representations of the dataset. Clustering techniques like k-medoids or hierarch...
- Autores:
-
Castiblanco Rodríguez, Juan Camilo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2020
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/51546
- Acceso en línea:
- http://hdl.handle.net/1992/51546
- Palabra clave:
- Difractogramas
Difracción de rayos X
Aprendizaje no supervisado
Aprendizaje automático (Inteligencia artificial)
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
| Summary: | In the present thesis starting from the dissimilarity introduced by Nicolás López, non-supervised algorithms are applied with the objective of finding natural groupings in the data of diffractograms and obtaining visual representations of the dataset. Clustering techniques like k-medoids or hierarchical clustering and also data representation algorithms like graph-oriented visualizations are implemented. |
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