CABRA: Clustering algorithm based on regular arrangement

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http://hdl.handle.net/2183/38006
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- Investigación (FIC) [1654]
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CABRA: Clustering algorithm based on regular arrangementAutor(es)
Fecha
2024Cita bibliográfica
Jorge, C. (2024). CABRA: Clustering algorithm based on regular arrangement. Operations Research Letters, 107137. https://doi.org/10.1016/j.orl.2024.107137
Resumen
[Abstract]: Clustering is an unsupervised learning technique for organizing complex datasets into coherent groups. A novel clustering algorithm is presented, with a simple grouping concept depending on only one hyperparameter, which makes it suitable for further extensions to any topology and space. It is compared to state-of-the-art algorithms, overall achieving a better performance independently on the structure and complexity of the data, making the proposed algorithm a valuable tool for real applications such as market segmentation, sentiment analysis and anomaly detection.
Palabras clave
Clustering
Segmentation
Classification
Outlier detection
Segmentation
Classification
Outlier detection
Versión del editor
Derechos
Atribución 4.0 Internacional (CC-BY)
ISSN
0167-6377 (print)
1872-7468 (electronic)
1872-7468 (electronic)