CABRA: Clustering algorithm based on regular arrangement
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http://hdl.handle.net/2183/38006
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CABRA: Clustering algorithm based on regular arrangementAuthor(s)
Date
2024Citation
Jorge, C. (2024). CABRA: Clustering algorithm based on regular arrangement. Operations Research Letters, 107137. https://doi.org/10.1016/j.orl.2024.107137
Abstract
[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.
Keywords
Clustering
Segmentation
Classification
Outlier detection
Segmentation
Classification
Outlier detection
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Rights
Atribución 4.0 Internacional (CC-BY)
ISSN
0167-6377 (print)
1872-7468 (electronic)
1872-7468 (electronic)