Método heurístico para particionamiento óptimo
保存先:
| 著者: | , , , |
|---|---|
| フォーマット: | artículo original |
| 状態: | Versión publicada |
| 出版日付: | 2003 |
| その他の書誌記述: | Many data analysis problems deal with non supervised partitioning of a data set, in non empty clusters well separated between them and homogeneous within the clusters. An ideal partitioning is obtained when any object can be assigned a class without ambiguity. The present paper has two main parts; first, we present different methods and heuristics that find the number of clusters for optimal partitioning of a set; afterwards, we propose a new heuristic and we perform different comparisons in order to evaluate the advantages on well known data sets; we end the paper with some concluding remarks. |
| 国: | Portal de Revistas UCR |
| 機関: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| 言語: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/221 |
| オンライン･アクセス: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/221 |
| Access Level: | acceso abierto |
| キーワード: | Optimal partitioning clustering classification heuristics Particionamiento óptimo clasificación heurísticas |