Weight Pair Group Average Mean Clustering for Interval-valued Data

Autor:	Sergio Galdino, Paulo Maciel
Rok vydání:	2019
Předmět:	Group (mathematics) business.industry Pattern recognition Interval valued Hierarchical clustering Interval arithmetic Euclidean distance ComputingMethodologies_PATTERNRECOGNITION Range (statistics) Artificial intelligence Uncertainty quantification Cluster analysis business Mathematics
Zdroj:	LA-CCI
DOI:	10.1109/la-cci47412.2019.9037035
Popis:	Weight Pair Group Average Mean clustering is one of several methods of agglomerative hierarchical clustering. It is a very popular method for computing hierarchical clusterings. Currently, clustering methods rely dissimilarity measures for interval-valued data uses representative point distance. Our work apply Weight Pair Group Average Mean clustering to interval-valued data based on the Range Euclidean Metric is an reliable alternative to be used to uncertainty quantification from symbolic interval-valued data.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7175da35ec536542278013cfbf510674 https://doi.org/10.1109/la-cci47412.2019.9037035 Zobrazit plný text záznamu