k-medianoids Clustering Algorithm
DOI :
https://doi.org/10.32473/flairs.36.133379Mots-clés :
Clustering medianoidRésumé
One of the simplest and popular clustering method is the simple k-means clustering algorithm. One of the drawbacks of the method is its sensitivity to outliers. To overcome this problem, the k-medians clustering algorithm is used. Another limitation of the simple k-means clustering algorithm is the Euclidean space assumption. The k-medoids has been used to overcome this assumption. Here a combined method called the k-medianoids clustering algorithm is proposed. A medianoid is a kind of median that does not require the Euclidean space assumption and is formally defined. The proposed method is demonstrated using nucleotide sequences.
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© James Cha, Teryn Cha, Sung-Hyuk Cha 2023
Cette œuvre est sous licence Creative Commons Attribution - Pas d'Utilisation Commerciale 4.0 International.