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)
Data
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
Resumo
[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 chave
Clustering
Segmentation
Classification
Outlier detection
Segmentation
Classification
Outlier detection
Versión do editor
Dereitos
Atribución 4.0 Internacional (CC-BY)
ISSN
0167-6377 (print)
1872-7468 (electronic)
1872-7468 (electronic)