Towards expert-inspired automatic criterion to cut a dendrogram for real-industrial applications
Visualitza/Obre
Cita com:
hdl:2117/373683
Tipus de documentText en actes de congrés
Data publicació2021
EditorIOS Press
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial 4.0 Internacional
Abstract
Hierarchical clustering is one of the most preferred choices to understand the underlying structure of a dataset and defining typologies, with multiple applications in real life. Among the existing clustering algorithms, the hierarchical family is one of the most popular, as it permits to understand the inner structure of the dataset and find the number of clusters as an output, unlike popular methods, like k-means. One can adjust the granularity of final clustering to the goals of the analysis themselves. The number of clusters in a hierarchical method relies on the analysis of the resulting dendrogram itself. Experts have criteria to visually inspect the dendrogram and determine the number of clusters. Finding automatic criteria to imitate experts in this task is still an open problem. But, dependence on the expert to cut the tree represents a limitation in real applications like the fields industry 4.0 and
additive manufacturing. This paper analyses several cluster validity indexes in the context of determining the suitable number of clusters in hierarchical clustering. A new Cluster Validity Index (CVI) is proposed such that it properly catches the implicit criteria used by experts when analyzing dendrograms. The proposal has been applied on a range of datasets and validated against experts ground-truth overcoming the results obtained by the State of the Art and also significantly reduces the computational cost .
CitacióSuman, S.; Karna, A.; Gibert, K. Towards expert-inspired automatic criterion to cut a dendrogram for real-industrial applications. A: International Conference of the Catalan Association for Artificial Intelligence. "Artificial Intelligence Research and Development: proceedings of the 23rd International Conference of the Catalan Association for Artificial Intelligence". Amsterdam: IOS Press, 2021, p. 235-244. ISBN 978-1-64368-211-2. DOI 10.3233/FAIA210140.
ISBN978-1-64368-211-2
Versió de l'editorhttps://ebooks.iospress.nl/volumearticle/57718
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FAIA-339-FAIA210140 (1).pdf | 498,8Kb | Visualitza/Obre |